Semiconductors such as silicon are the cornerstone of today’s essential technologies; however, the variety of materials available to power devices is limited. While metal oxides are durable, only a small subset is semiconducting as they are naturally insulators.

Researchers from Carnegie Mellon University and Penn State University have made a breakthrough by which they have successfully transformed an insulating metal oxide into a high-performance semiconductor by using a technique called high-entropy mixing. Developing a complex mixture of manganese, iron, cobalt, nickel, copper, and zinc into a tungsten oxide framework within a single crystal structure, called wolframite, the researchers intentionally created a state of high configurational entropy. The new material, A⁶WO₄, possesses both semiconducting properties and ultra-low thermal conductivity, making it an ideal formulation for thermoelectric devices.

Ride-hailing has become a routine part of urban life in the United States, but its broader economic impacts have been difficult to measure. As Uber and Lyft expanded across hundreds of cities over the past decade, they promised more flexible work for drivers and convenience for passengers. Questions remained, however, about how these promises translated into measurable changes in local economies.

A new study from Carnegie Mellon University set out to provide an answer by analyzing the launch of ridesharing services across 167 metropolitan areas between 2010 and 2019. Because the entrance of these transportation network services (TNCs) was staggered, the team was able to compare economic trends before and after TNC entry while accounting for differences across regions.

By combining publicly available workforce and economic analysis data with modern difference-in-differences methods designed for policies that roll out over time, researchers identified a consistent pattern. After Uber and Lyft entered the region, two indicators shifted: regional GDP per capita increased, and the number of seasonal, temporary, or intermittent jobs rose. And, while they did not observe statistically significant effects on overall employment or wages, these shifts suggest that ride-hailing expanded access to flexible work and unlocked new economic activity tied to increased mobility.

“Uber and Lyft have made a lot of claims over the years about boosting citywide economies and providing flexible jobs,” said Jeremy Michalek, professor of engineering and public policy and mechanical engineering. “We find that the data do, in fact, corroborate some of these claims with evidence that Uber and Lyft have increased intermittent employment and economic output in US cities as they entered.”

The findings, published in Nature Cities, extend beyond ride-hailing. The rise in unstable employment without a corresponding rise in total employment highlights how gig-economy platforms can reshape labor markets by changing when and how people work. Increases in GDP also point to broader economic ripple effects: passengers take trips they otherwise might not, workers travel to jobs more easily, and cities experience new patterns of consumption and activity.

Concert stages may look effortless when the curtain rises, but backstage they are giant mechanical systems filled with moving parts, tight timelines, and constant problem-solving.

At Carnegie Mellon University, students are learning how to tackle those challenges firsthand through Entertainment Engineering, a new course that combines mechanical engineering and theater production to solve fundamental problems for the live entertainment industry.

Developed jointly by professors Phil LeDuc and Mark Bedillion from the Department of Mechanical Engineering and Kevin Hines and David Boevers from the School of Drama, Entertainment Engineering brings students together from two fields that rarely overlap in the classroom but constantly intersect behind the scenes of live productions.

In its first semester, students collaborated on a challenge sponsored by TAIT, the global company behind staging and automation systems used in concerts for artists like Taylor Swift, theater productions on Broadway and the West End, and live events around the world including the Olympics. The company itself has strong roots at CMU as its CEO Adam Davis and dozens of its employees are CMU alumni.

For decades, monitoring cardiovascular health has required some combination of cuffs, sticky electrodes, wearable sensors, and frequent doctor visits. A new experimental system suggests the future of heart monitoring may look less like a hospital, and more like a smart speaker sitting quietly on a shelf at home.

Researchers from Carnegie Mellon University’s College of Engineering have developed an AI-powered millimeter-wave radar platform capable of tracking blood-flow dynamics across the human body without making physical contact. The prototype system, called PolyPulse, uses the same class of radar technology found in autonomous vehicles and consumer electronics to measure subtle bodily movements caused by cardiac activity. The result is a compact device that can estimate pulse transit time, a key marker of arterial stiffness, and even infer diastolic blood pressure remotely.

“The implications are potentially enormous,” says Jiangyifei Zhu, a Ph.D. student in electrical and computer engineering and co-lead author of the paper.

“Cardiovascular disease remains the leading cause of death globally, and many of its warning signs develop gradually over years. By detecting these changes early at home could dramatically improve outcomes.”

The Water Resources Development Act (WRDA) of 2024 outlines federal priorities for conserving and developing U.S. water resources and infrastructure. One growing priority is ensuring that water treatment systems can remove per- and polyfluoroalkyl substances (PFAS), often referred to as “forever chemicals,” from public drinking water.

“PFAS are synthetic chemicals that can persist in water and accumulate over time, which can be harmful to humans when ingested in large amounts,” says Pingbo Tang, associate professor of civil and environmental engineering. “The Environmental Protection Agency is regulating water treatment nationwide to ensure that water utilities achieve a certain level of PFAS compliance to protect the health of the community.”

Designing systems to remove PFAS from drinking water is a complex engineering challenge because conventional treatment is often ineffective, and regulations are tightening. Engineers typically adapt established technologies—such as granular activated carbon, ion exchange, and membranes—but must re‑optimize them for PFAS behavior and new regulatory limits, often based on site‑specific pilot testing and evolving design guidance.

To address this challenge, CMU researchers are collaborating with industry partners Circular Water Solutions, LLC and Ethos Collaborative to help water utilities move more quickly from design concept to engineered systems and deployable infrastructure.

Jinghua Xiao, president and principal engineer at Circular Water Solution, LLC, served as the project’s environmental engineer. She brought extensive experience in environmental issues and water chemistry to address the regulatory specifications for PFAS systems.

“Dr. Xiao is the domain scientist on this project,” says Tang. “She provided our team data to analyze the relationship between chemical doses and the treatment speed of the water—calculations that are EPA-regulated and therefore critical to testing your design.”

Meanwhile, Damon Weiss, a civil engineer at Ethos Collaborative, contributed his expertise in water infrastructure design and engineering to the project.

“We are leveraging Damon’s expertise to build a digital twin of CMU’s campus to understand how sewage systems generate wastewater and how wastewater should be treated,” says Tang. “This analysis of an existing sewage system helped us build a knowledge base for differentiating between good and poor engineering design.”

Tang explains that support from industry partners helps researchers tackle what engineers call an ill‑defined problem—one where existing treatment technologies must be re‑engineered and integrated under new regulatory constraints and site‑specific conditions. Rather than designing PFAS systems entirely from scratch, engineers face a tedious, iterative process of adapting and optimizing available options into deployable treatment trains, a task that increasingly requires digital computational tools to coordinate design–engineering collaboration.

The project investigated how artificial intelligence can streamline the design process for PFAS treatment systems. By analyzing how high-performing engineering teams communicate during the design process, the researchers hope to identify strategies that help water utilities move more quickly from concept to deployable infrastructure. Communication gaps between teams of environmental engineers (process designers) and mechanical engineers can lead to repeated design iterations, slowing the delivery of deployable solutions.

“What we are trying to do is observe both high-performing teams and teams that struggle with communication,” says Tang. “By studying how these groups exchange information, we hope to identify communication patterns that help teams reduce the number of design revisions needed to reach a final solution of mechanical systems design that properly implements the process design subject to all engineering constraints.”

When visiting a theme park, guests don’t think about what made their favorite character blink or smile, they just feel the magic of their favorite story coming to life. That’s by design.

As an Imagineer at Walt Disney World, Lori Kipp (MechE ’21) works behind the scenes to design the systems that make that magic possible. Her work lives at the intersection of engineering precision and storytelling restraint to make sure that nothing mechanical ever pulls guests out of the story.

More than 100 years ago, Andrew Carnegie founded the Carnegie Technical Schools to provide practical, technical education to workers in Pittsburgh, many of whom worked in steel mills and other manufacturing operations.

While that school is now an elite university that trains leading engineers and computer scientists, manufacturing workers are still learning core skills here.

Carnegie Mellon University’s Manufacturing Futures Institute (MFI) has joined Catalyst Connection and the Advanced Robotics for Manufacturing (ARM) Institute to create SkillMill19^TM, a new workforce training initiative designed to upskill local workers needed in increasingly technical manufacturing jobs.

More than 100 years ago, Andrew Carnegie founded the Carnegie Technical Schools to provide practical, technical education to workers in Pittsburgh, many of whom worked in steel mills and other manufacturing operations.

While that school is now an elite university that trains leading engineers and computer scientists, manufacturing workers are still learning core skills here.

Carnegie Mellon University’s Manufacturing Futures Institute (MFI) has joined Catalyst Connection and the Advanced Robotics for Manufacturing (ARM) Institute to create SkillMill19^TM, a new workforce training initiative designed to upskill local workers needed in increasingly technical manufacturing jobs.

Gregory Lowry has been named head of the Department of Civil and Environmental Engineering at Carnegie Mellon University. Lowry is an internationally recognized leader in environmental nanotechnology and has served as the department’s interim head since January 1, 2026. Currently a Hamerschlag University Professor in CEE, Lowry has served as a faculty member for more than 25 years. Lowry brings to the role a record of scholarly achievement, research leadership, a deep commitment to teaching and mentoring, and long-standing service to the department.

That service includes his time on the department’s executive committee as executive director of new initiatives. In that role, he led the Center for Engineering Resilience and Climate Adaptation (CERCA), which unites faculty and students across the university to develop resilient, equitable, and adaptive solutions for infrastructure, energy, transportation, and water systems facing a changing climate. He also developed new opportunities for the department to expand its educational offerings through online certificate programs 

Beyond Carnegie Mellon, Lowry has shaped the field of environmental nanotechnology for more than two decades, leading multidisciplinary research initiatives supported by the U.S. Department of Defense, Department of Energy, Environmental Protection Agency, and National Science Foundation. From 2008 to 2019, he served as deputy director of the $30 million NSF/EPA-funded Center for Environmental Implications of Nanotechnology (CEINT), a research consortium spanning several partner universities. In 2020, he joined the editorial leadership of the American Chemical Society journal Environmental Science & Technology as an executive and associate editor.

Lowry is a fellow of the American Association for the Advancement of Science and the Association of Environmental Engineering and Science Professors.

As head, Lowry will lead the department’s continued focus on engineering resilience to sustain a changing world.

Gregory Lowry has been named head of the Department of Civil and Environmental Engineering at Carnegie Mellon University. Lowry is an internationally recognized leader in environmental nanotechnology and has served as the department’s interim head since January 1, 2026. Currently a Hamerschlag University Professor in CEE, Lowry has served as a faculty member for more than 25 years. Lowry brings to the role a record of scholarly achievement, research leadership, a deep commitment to teaching and mentoring, and long-standing service to the department.

That service includes his time on the department’s executive committee as executive director of new initiatives. In that role, he led the Center for Engineering Resilience and Climate Adaptation (CERCA), which unites faculty and students across the university to develop resilient, equitable, and adaptive solutions for infrastructure, energy, transportation, and water systems facing a changing climate. He also developed new opportunities for the department to expand its educational offerings through online certificate programs 

Beyond Carnegie Mellon, Lowry has shaped the field of environmental nanotechnology for more than two decades, leading multidisciplinary research initiatives supported by the U.S. Department of Defense, Department of Energy, Environmental Protection Agency, and National Science Foundation. From 2008 to 2019, he served as deputy director of the $30 million NSF/EPA-funded Center for Environmental Implications of Nanotechnology (CEINT), a research consortium spanning several partner universities. In 2020, he joined the editorial leadership of the American Chemical Society journal Environmental Science & Technology as an executive and associate editor.

Lowry is a fellow of the American Association for the Advancement of Science and the Association of Environmental Engineering and Science Professors.

As head, Lowry will lead the department’s continued focus on engineering resilience to sustain a changing world.

Gregory Lowry has been named head of the Department of Civil and Environmental Engineering at Carnegie Mellon University. Lowry is an internationally recognized leader in environmental nanotechnology and has served as the department’s interim head since January 1, 2026. Currently a Hamerschlag University Professor in CEE, Lowry has served as a faculty member for more than 25 years. Lowry brings to the role a record of scholarly achievement, research leadership, a deep commitment to teaching and mentoring, and long-standing service to the department.

That service includes his time on the department’s executive committee as executive director of new initiatives. In that role, he led the Center for Engineering Resilience and Climate Adaptation (CERCA), which unites faculty and students across the university to develop resilient, equitable, and adaptive solutions for infrastructure, energy, transportation, and water systems facing a changing climate. He also developed new opportunities for the department to expand its educational offerings through online certificate programs 

Beyond Carnegie Mellon, Lowry has shaped the field of environmental nanotechnology for more than two decades, leading multidisciplinary research initiatives supported by the U.S. Department of Defense, Department of Energy, Environmental Protection Agency, and National Science Foundation. From 2008 to 2019, he served as deputy director of the $30 million NSF/EPA-funded Center for Environmental Implications of Nanotechnology (CEINT), a research consortium spanning several partner universities. In 2020, he joined the editorial leadership of the American Chemical Society journal Environmental Science & Technology as an executive and associate editor.

Lowry is a fellow of the American Association for the Advancement of Science and the Association of Environmental Engineering and Science Professors.

As head, Lowry will lead the department’s continued focus on engineering resilience to sustain a changing world.

Gregory Lowry has been named head of the Department of Civil and Environmental Engineering at Carnegie Mellon University. Lowry is an internationally recognized leader in environmental nanotechnology and has served as the department’s interim head since January 1, 2026. Currently a Hamerschlag University Professor in CEE, Lowry has served as a faculty member for more than 25 years. Lowry brings to the role a record of scholarly achievement, research leadership, a deep commitment to teaching and mentoring, and long-standing service to the department.

That service includes his time on the department’s executive committee as executive director of new initiatives. In that role, he led the Center for Engineering Resilience and Climate Adaptation (CERCA), which unites faculty and students across the university to develop resilient, equitable, and adaptive solutions for infrastructure, energy, transportation, and water systems facing a changing climate. He also developed new opportunities for the department to expand its educational offerings through online certificate programs 

Beyond Carnegie Mellon, Lowry has shaped the field of environmental nanotechnology for more than two decades, leading multidisciplinary research initiatives supported by the U.S. Department of Defense, Department of Energy, Environmental Protection Agency, and National Science Foundation. From 2008 to 2019, he served as deputy director of the $30 million NSF/EPA-funded Center for Environmental Implications of Nanotechnology (CEINT), a research consortium spanning several partner universities. In 2020, he joined the editorial leadership of the American Chemical Society journal Environmental Science & Technology as an executive and associate editor.

Lowry is a fellow of the American Association for the Advancement of Science and the Association of Environmental Engineering and Science Professors.

As head, Lowry will lead the department’s continued focus on engineering resilience to sustain a changing world.

A silicone material called PDMS has become foundational to technologies ranging from soft robots that safely grasp fragile objects to wearable sensors that flex naturally with the body.  The material is prized for its flexibility, durability, and biocompatibility but despite its widespread use, creating intricate and arbitrary microscale structures of it has been a manufacturing challenge—until now.

Researchers at Carnegie Mellon University have developed a way to print detailed 2D and 3D PDMS architectures with remarkable precision using aerosol jet printing. This creates new possibilities for soft electronics, biomedical devices and next-generation robotics.

Published in npj Advanced Manufacturing, the study demonstrates how the team successfully fabricated everything from microscopic lines and pillars to complex lattices and soft microfluidic channels without the molds and labor-intensive fabrication steps typically required in soft material manufacturing.

The work was led by Rahul Panat, professor of mechanical engineering, and Swastik Kushagr, Ph.D. candidate in Panat’s lab, alongside collaborators across materials science and robotics.

Understanding data structures and algorithms is challenging, and so is finding the right job. That’s why a decade ago, the students at Carnegie Mellon University Silicon Valley established the Coding Gym, a weekly, drop-in gathering where students strengthen their technical chops and support each other as they navigate the employment process.

A goal of these student-led sessions is to bolster collaborative problem-solving; however, occasionally guest speakers are invited to share industry views. Case in point: Riyaz Rafi Ahmed, a security engineer at NVIDIA and an alumnus from Carnegie Mellon’s Information Networking Institute.

In March, Ahmed led a special guest session, titled “Security Engineering: Career Path + Industry Insights,” which focused on security engineering and the broader landscape of cybersecurity. Ahmed was invited by Aadhil Mubarak Syed, a Coding Gym co-lead along with Ephron Wu. Both students serve as Peer Career Consultants and are pursuing master’s degrees in software engineering in the Department of Electrical and Computer Engineering.

When Mubarak Syed was considering CMU-SV for his graduate work, he talked to Ahmed about the program at a student-alumni mixer. “Since we shared a similar cultural and personal background, our friendship grew, and we kept in touch regularly in the following months,” says Mubarak Syed. Thanks to Mubarak Syed’s invitation, Ahmed returned to campus once again to share insights from his own experience in the field. “Students came away with a clearer understanding of security engineering as a broad and multidisciplinary field.”

Ahmed’s presentation walked students through major cybersecurity domains, such as security architecture, application security, security operations, threat intelligence, compliance, and risk management, and he discussed how they fit together in industry. He offered advice on different entry points into security for students with software engineering backgrounds.

According to Mubarak Syed, the session expanded the students’ perspectives beyond traditional software engineering roles. “Ahmed’s talk highlighted that security engineering is not a single path, but a collection of interconnected domains, which helped students better understand where they might fit within that landscape.”

“It was valuable for students to hear directly from someone working in the field, especially in a role that intersects with emerging areas like AI security,” said Mubarak Syed. “That real-world context made the concepts more tangible and actionable.”

Carnegie Mellon University Africa (CMU-Africa) alumnus Jean Pierre “Petero” Niyodusenga (MSIT ’14) is on a mission to help train African youth to work in cybersecurity to ensure Rwanda meets its goal of becoming a secure, knowledge-based economy. Large scale training aligns with Rwanda’s National Cyber Security Strategy and Vision 2050. The plan notes that cyberattacks will continue to grow, and currently there are fewer than 300,000 cybersecurity professionals to combat these cyberthreats.

Training and mentoring youth to fill the growing need for workforce in cybersecurity and related fields is a personal passion for Niyodusenga, a cybersecurity expert, entrepreneur, and educator, who considers himself a bridge between academia and industry.

“In Rwanda we are looking forward to becoming a knowledge-based economy by the year 2030. This can only happen if we build the capacity now to secure a digital infrastructure. Who is going to actually provide that security? It’s the young people,” Niyodusenga said. “We have to start educating and training young people now, not just in Rwanda, or Africa, but across the world.”

Radio telescopes give us a glimpse into the cosmos. Detecting faint radio waves from stars, galaxies, and black holes, these instruments allow scientists to monitor the universe without interruption. Despite their size, radio telescopes are designed to detect extremely weak cosmic signals. Because of this high sensitivity, even low-power local radio interference can dominate the signal and mask the astronomical data.

Radio quiet zones (RQZs) are essential for the operation of radio telescopes. With legal restrictions on WiFi, Bluetooth, cell phones, and radio broadcasts, RQZs protect sensitive radio astronomy telescopes and military intelligence equipment from interference. However, despite layers of regulation, the quiet is breaking down. Over the past few years, there has been an increased proliferation of various terrestrial wireless communication technologies around the world. Consumer electronics, like phones and routers, constantly leak energy across the spectrum. Just a faint, persistent signal from a faulty device, like a microwave oven miles away, can blur the data from a distant galaxy, or mask the signature of a pulsar entirely.

Traditionally, tracking down these rogue signals has been time-consuming. Engineers load up trucks with spectrum analyzers and drive, triangulating signals based on power readings. It’s slow, expensive, and deeply human.

Animals move with a level of precision and adaptability that robots struggle to match. In Carnegie Mellon University’s Department of Mechanical Engineering, researchers are developing a new AI-driven approach to uncover how brains and bodies work together. By turning complex biological systems into models that can be tested and refined, the team seeks to understand and replicate animal performance in robotic systems.

One focus of The Biohybrid and Organic Robotics Lab are neuromechanical models that simulate how neural signals and physical movement continuously inform one another. These models are powerful, but difficult to build because with countless parameters, even the smallest miscalculation can lead to large gaps between simulated behavior and what researchers observe in real animals.

“Biological systems are incredibly complex,” said Camila Fernandez, Ph.D. candidate in the department of mechanical engineering. “We’re trying to model something where everything affects everything, and it’s not always clear which piece we need to adjust when outcomes don’t match predictions.”

To address this, the team developed a systematic, data-driven framework that removes much of the guesswork. Traditionally, improving these models relied heavily on experts manually tweaking parameters, running experiments, and then comparing results in a very time-consuming cycle. The new method introduces a reinforcement learning algorithm that acts like a digital twin of the model with a built-in guide.

“It’s like having a coach for your model,” explained Fernandez. “It tells us, ‘This parameter is underperforming, so you should focus your refinements here.’”

The system can quantitatively identify which parameters are most responsible for any discrepancies between real animal data, the original neuromechanical model, and the reinforcement learning driven digital twin.

“Notably, the system only adds complexity where absolutely necessary,” said Vickie Webster-Wood, associate professor of mechanical engineering. “Instead of making the entire model more complicated, the system identifies the specific parts that require more detail while keeping everything else as simple as possible. This approach reduces computational cost while improving accuracy.”

So far, the team has validated their approach using computational models and robotic analogs. While a direct, real-time comparison between animals and physical robots, rather than through a model, remains a challenge, the team plans to explore how they can apply this framework to physical robots. Ultimately, the goal is to accelerate discovery.

“There’s still so much we don’t understand,” Fernandez said. “We’re essentially looking at a black box and trying to figure out how it works. If we can speed up how we build and refine models, we can ask better, more targeted questions, and get closer to the answers.”

This research was published in npj Robotics.

Animals move with a level of precision and adaptability that robots struggle to match. In Carnegie Mellon University’s Department of Mechanical Engineering, researchers are developing a new AI-driven approach to uncover how brains and bodies work together. By turning complex biological systems into models that can be tested and refined, the team seeks to understand and replicate animal performance in robotic systems.

One focus of The Biohybrid and Organic Robotics Lab are neuromechanical models that simulate how neural signals and physical movement continuously inform one another. These models are powerful, but difficult to build because with countless parameters, even the smallest miscalculation can lead to large gaps between simulated behavior and what researchers observe in real animals.

“Biological systems are incredibly complex,” said Camila Fernandez, Ph.D. candidate in the department of mechanical engineering. “We’re trying to model something where everything affects everything, and it’s not always clear which piece we need to adjust when outcomes don’t match predictions.”

To address this, the team developed a systematic, data-driven framework that removes much of the guesswork. Traditionally, improving these models relied heavily on experts manually tweaking parameters, running experiments, and then comparing results in a very time-consuming cycle. The new method introduces a reinforcement learning algorithm that acts like a digital twin of the model with a built-in guide.

“It’s like having a coach for your model,” explained Fernandez. “It tells us, ‘This parameter is underperforming, so you should focus your refinements here.’”

The system can quantitatively identify which parameters are most responsible for any discrepancies between real animal data, the original neuromechanical model, and the reinforcement learning driven digital twin.

“Notably, the system only adds complexity where absolutely necessary,” said Vickie Webster-Wood, associate professor of mechanical engineering. “Instead of making the entire model more complicated, the system identifies the specific parts that require more detail while keeping everything else as simple as possible. This approach reduces computational cost while improving accuracy.”

So far, the team has validated their approach using computational models and robotic analogs. While a direct, real-time comparison between animals and physical robots, rather than through a model, remains a challenge, the team plans to explore how they can apply this framework to physical robots. Ultimately, the goal is to accelerate discovery.

“There’s still so much we don’t understand,” Fernandez said. “We’re essentially looking at a black box and trying to figure out how it works. If we can speed up how we build and refine models, we can ask better, more targeted questions, and get closer to the answers.”

This research was published in npj Robotics.

Early Career Professorships 

Early Career Professorships are awarded to junior faculty members whose research and teaching demonstrate exceptional promise. These professorships provide resources to advance their scholarly work and educational initiatives, enabling them to create exceptional learning experiences for students.

Marc Dandin

Early Career Professorships 

Early Career Professorships are awarded to junior faculty members whose research and teaching demonstrate exceptional promise. These professorships provide resources to advance their scholarly work and educational initiatives, enabling them to create exceptional learning experiences for students.

Marc Dandin

The National Science Foundation (NSF) has awarded the Faculty Early Career Development (CAREER) Award to Sarah Fakhreddine, Noelia Grande Gutiérrez, and Tathagata Srimani. Designed to support early-career faculty, the NSF CAREER award is a prestigious five-year grant that helps them serve as role models in education and research.

Sarah Fakhreddine, Assistant Professor, Civil and Environmental Engineering

Each year, more than half a million Americans experience limb loss or are born with limb difference, yet only a small fraction receives truly personalized prosthetic care. For many, choosing the right prosthetic foot relies less on data and more on trial and error or clinician’s intuition. Josh Caputo (B.S. MechE /ECE ’10, Ph.D. MechE ’15) encountered this challenge firsthand while pursuing his Ph.D. at Carnegie Mellon University and made it his mission to change the process. The result is Humotech, a company leveraging cutting-edge robotic emulation systems to empower patients and researchers to personalize prosthetic and exoskeleton design like never before.

While Caputo (B.S. MechE /ECE ’10, Ph.D. MechE ’15) didn’t set out to start his own company, he was drawn to engineering because of his interest in cars, bikes, and “anything with a motor.” As a new student, a tour of CMU’s labs solidified that the mechanical engineering department would be his home, particularly with a focus on robotics. It was from internships at NASA and a defense contractor that Caputo began to feel the itch of entrepreneurship. “I realized I wasn’t meant to be a small cog in a big machine,” he said. “And I wanted to build something that mattered, something human-centered.”

Caputo’s Ph.D. work laid the foundation for exactly that—Humotech’s signature innovation: a cable-driven emulation system that personalizes prosthetic and exoskeleton design.

“One of the first things I geeked out about was how a powered prosthetic foot could offer advantages over the low-tech options available,” he explained. Instead of building a new prototype for every experiment, Caputo developed a tethered system that allowed for rapid testing and personalized tailoring through software that adjusts for torque, force, and stiffness for patients in a matter of minutes.

More than 80 billion neurons in the human brain control our movement, perception, memory, decision-making, and emotions. These neurons can work independently, and they can also form dynamic, adaptable networks that operate both within and across dozens of brain regions, serving as the brain’s communication and computation system.

After having only been able to study one neuron at a time for many years, scientists and engineers can now study the interactions of many neurons within single regions of the brain, which has resulted in advances in neuroscience. But our ability to understand neuron interactions across those multiple regions still limits our understanding of the human brain.

The spiking activity of an individual neuron can be influenced by neurons within the same brain area, as well as neurons in other brain areas across wide areas of the brain. Many studies have examined the activity of populations of neurons within a single brain area. But since most brain functions rely on interactions across brain areas, it is likely that some component of the activity of each brain area is shaped by interactions with other brain areas.

Developments in neural recording technology have enabled simultaneous recordings of populations of neurons in multiple brain areas, which has given rise to the possibility of distinguishing interactions across brain areas from interactions solely within a single brain area. However, most statistical methods for analyzing populations of neurons are not designed to distinguish activity shared across areas from activity shared solely among neurons within each area.

The team, including lead authors Megan McDonnell, Akash Umakantha, and Ryan Williamson, developed a novel statistical approach called pCCA-FA that will allow researchers to leverage recordings from multiple areas of the brain at one time, revealing aspects of brain functions that are hidden in single-area recordings. This work was recently published in Nature Communications.

The relatively new ability to record neurons in multiple areas of the brain simultaneously allowed the team to record neurons in both hemispheres of the prefrontal cortex in animals performing a spatial memory task.

The prefrontal cortex serves as the brain’s control center and is responsible for many advanced mental abilities, including working memory.

By applying their statistical method to both data from their recordings, as well as synthetic data, they were able to tease apart the global processing from the local interactions, and to show whether fluctuations in neuron activity were shared within or across areas of the brain.

They found substantial activity that was shared among neurons within each population, much of which was actually shared across hemispheres of the prefrontal cortex and linked to an arousal process. Their work presents a path by which we can leverage multi-area recordings to reveal aspects of brain functions that are hidden in single-area recordings.

Fifty-three College of Engineering students have been awarded presidential and graduate fellowships for the 2025–2026 academic year. These prestigious awards provide financial support for some of Carnegie Mellon’s top students in their studies and research.

Claire and John Bertucci Fellowship in Engineering

Established by Claire R. (MM 1965) and John R. (ENG 1963, TPR 1965) Bertucci in 2006, this fund provides merit fellowships to graduate students pursuing doctoral degrees in engineering.

• Colin Ancalmo, Mechanical Engineering
• Sarah Birchall, Materials Science Engineering
• Camila Cue, Chemical Engineering
• Crestienne DeChaine, Materials Science Engineering
• Hailey Hall, Materials Science Engineering
• Melanie Huq, Engineering and Public Policy
• Jingyan Li, Civil and Environmental Engineering
• Seongeun Park, Civil and Environmental Engineering
• Daniel Pert, Chemical Engineering
• Corrinne Smith-Lewis, Mechanical Engineering
• Emerson Uhlig, Chemical Engineering
• Daniel Ovalle Varela, Chemical Engineering

Phillips and Huang Family Fellowship in Energy

Established by Michael S. Phillips (ENG 1982) and his wife, Caroline B. Huang, in 2013 to support College of Engineering doctoral students researching energy innovation.

• Bashu Aman, Mechanical Engineering
• Tamar Moss, Engineering and Public Policy

Ronald F. and Janice A. Zollo Fellowship

Established by Ronald F. Zollo, Ph.D. (ENG 1963, 1966, 1971), in 2017 to support graduate students in the College of Engineering, with preference for students whose research is related to neuroscience or neuroengineering.

• Martin Goessweiner, Biomedical Engineering

Neil and Jo Bushnell Fellowship in Engineering

Established by Dr. Michael L. Bushnell (ENG 1983, 1986) in 2008 to support graduate students in engineering, with a preference for doctoral students working in nanotechnology or electronic materials.

• Shravan Godse, Mechanical Engineering
• Tianyi Huang, Mechanical Engineering
• Ellen Otto, Biomedical Engineering
• Mihailo Rancic, Electrical and Computer Engineering

Maggie and Bob Gregory Endowed Engineering Fellowship

Established by Margaret E. Gregory (ENG 1961) in 2020 to support graduate students in the College of Engineering, with a preference for students who have demonstrated a commitment to the advancement of women in the field of engineering.

• Carolina Colombo Tedesco, Chemical Engineering

Liang Ji-Dian Fellowship

Established in 1980 by Ting-Lung Liang in honor of his father to support graduate students in the College of Engineering.

• Hua Tong, Mechanical Engineering
• Jason Yao, Chemical Engineering
• Jiangyifei Zhu, Electrical and Computer Engineering

David Barakat and LaVerne Owen-Barakat Fellowship

Established by David H. Barakat (ENG 1968) and LaVerne Owen-Barakat in 2013 to support graduate students in the College of Engineering.

• Nayesha Gandotra, Mechanical Engineering
• Orkun Irsoy, Electrical and Computer Engineering

Bradford and Diane Smith Fellowship in Engineering

Established by Bradford L. (ENG 1969) and Diane J. Smith (DC 1971) in 2010 to support doctoral students in the College of Engineering.

• Leia Jiang, Biomedical Engineering
• Shidhartho Roy, Biomedical Engineering

ATK-Nick G. Vlahakis Fellowship

Established in 2003 by the ATK Foundation in honor of Nick G. Vlahakis (ENG 1974), this fund provides support for master's degree candidates in mechanical engineering, electrical and computer engineering, or materials science and engineering, or to students pursuing a joint MBA/B.S. in engineering within the aforementioned departments.

• Holly Chen, Mechanical Engineering
• Zachary Kushnir, Mechanical Engineering
• Junil Min, Mechanical Engineering

Presidential Fellowship

The College of Engineering recognizes high-achieving Ph.D. students with a Presidential Fellowship, covering an entire year of tuition.

• Joel Disu, Biomedical Engineering
• Miaosi Dong, Civil and Environmental Engineering
• Zhixiong Li, Mechanical Engineering
• Catalina Montoya, Biomedical Engineering
• Tejus Surendran, Biomedical Engineering
• Yi Yang, Materials Science Engineering

Wei Shen and Xuehong Zhang Presidential Fellowship

Established by Wei Shen and Xuehong Zhang in 2019 to provide fellowship support for graduate students enrolled in electrical and computer engineering. Wei Shen and Xuehong Zhang are parents of Chen Shen (ENG 2022).

• Artharva Raut, Electrical and Computer Engineering
• Zhaoyi Zhou, Electrical and Computer Engineering

Richard King Mellon Foundation Presidential Fellowship in Energy

Established by the Richard King Mellon Foundation in 2014 to support outstanding graduate students who conduct energy research.

• Ian Martin, Chemical Engineering
• Haoran Ni, Materials Science and Engineering

Ruth Furman Miller and David H. Miller Presidential Fellowship in the Department of Civil and Environmental Engineering

Established by Ruth Furman Miller (MM 1942) through her estate to support graduate students enrolled in the College of Engineering's Department of Civil and Environmental Engineering.

• Maximiliano Larrain Silva, Civil and Environmental Engineering

Thomas and Maria Fok Presidential Fellowship in the Department of Civil and Environmental Engineering

Established by Thomas D.Y. Fok, Ph.D. (ENG 1956) in 2017 to support graduate students enrolled in the Department of Civil and Environmental Engineering.

• Abias Nabimanya, Civil and Environmental Engineering

CyLab Presidential Fellow

CyLab Security and Privacy Institute recognizes high-achieving Ph.D. students pursuing security and/or privacy-related research with a CyLab Presidential Fellowship, covering an entire year of tuition.

• Elijah Bouma-Sims, Software and Societal Systems
• Hao-Ping (Hank) Lee, Human-Computer Interaction
• Terrance Liu, Machine Learning
• Alexandra Nisenoff, Software and Societal Systems
• Hugo Sadok, Computer Science
• Rose Silver, Computer Science
• Taro Tsuchiya, Software and Societal Systems

Heinz Endowments-Lowell Steinbrenner Presidential Graduate Fellowship in Sustainability Science

Established in 2014 through a combination of support from the Heinz Endowments, the Steinbrenner Institute for Environmental Education and Research (SEER) and CMU, this fund is a tribute to Lowell Steinbrenner, a pioneer of environmental education and research, and recognizes outstanding graduate students with exceptional potential to make an impact in sustainability science over the course of their careers.

• Nana Oye Ndaase Djan, Engineering and Public Policy

K&L Gates Presidential Fellowship

Established in 2016 by K&L Gates, LLP to support graduate students whose studies relate to the field of ethics and computational science and technology, and who are enrolled in programs leading to a Ph.D. degree at CMU.

• Che-Yu Lin, Civil and Environmental Engineering

TCS Presidential Fellowship

Established in 2015 by Tata Consultancy Services Limited to support graduate students enrolled at Carnegie Mellon University.

• Mangalam Sahai, Mechanical Engineering

James Sprague Presidential Fellowship

Established by James Sprague (ENG 1909) to provide support to graduate students enrolled in the College of Engineering.

• Hanjiang Hu, Electrical and Computer Engineering

Fifty-three College of Engineering students have been awarded presidential and graduate fellowships for the 2025–2026 academic year. These prestigious awards provide financial support for some of Carnegie Mellon’s top students in their studies and research.

Claire and John Bertucci Fellowship in Engineering

Established by Claire R. (MM 1965) and John R. (ENG 1963, TPR 1965) Bertucci in 2006, this fund provides merit fellowships to graduate students pursuing doctoral degrees in engineering.

• Colin Ancalmo, Mechanical Engineering
• Sarah Birchall, Materials Science Engineering
• Camila Cue, Chemical Engineering
• Crestienne DeChaine, Materials Science Engineering
• Hailey Hall, Materials Science Engineering
• Melanie Huq, Engineering and Public Policy
• Jingyan Li, Civil and Environmental Engineering
• Seongeun Park, Civil and Environmental Engineering
• Daniel Pert, Chemical Engineering
• Corrinne Smith-Lewis, Mechanical Engineering
• Emerson Uhlig, Chemical Engineering
• Daniel Ovalle Varela, Chemical Engineering

Phillips and Huang Family Fellowship in Energy

Established by Michael S. Phillips (ENG 1982) and his wife, Caroline B. Huang, in 2013 to support College of Engineering doctoral students researching energy innovation.

• Bashu Aman, Mechanical Engineering
• Tamar Moss, Engineering and Public Policy

Ronald F. and Janice A. Zollo Fellowship

Established by Ronald F. Zollo, Ph.D. (ENG 1963, 1966, 1971), in 2017 to support graduate students in the College of Engineering, with preference for students whose research is related to neuroscience or neuroengineering.

• Martin Goessweiner, Biomedical Engineering

Neil and Jo Bushnell Fellowship in Engineering

Established by Dr. Michael L. Bushnell (ENG 1983, 1986) in 2008 to support graduate students in engineering, with a preference for doctoral students working in nanotechnology or electronic materials.

• Shravan Godse, Mechanical Engineering
• Tianyi Huang, Mechanical Engineering
• Ellen Otto, Biomedical Engineering
• Mihailo Rancic, Electrical and Computer Engineering

Maggie and Bob Gregory Endowed Engineering Fellowship

Established by Margaret E. Gregory (ENG 1961) in 2020 to support graduate students in the College of Engineering, with a preference for students who have demonstrated a commitment to the advancement of women in the field of engineering.

• Carolina Colombo Tedesco, Chemical Engineering

Liang Ji-Dian Fellowship

Established in 1980 by Ting-Lung Liang in honor of his father to support graduate students in the College of Engineering.

• Hua Tong, Mechanical Engineering
• Jason Yao, Chemical Engineering
• Jiangyifei Zhu, Electrical and Computer Engineering

David Barakat and LaVerne Owen-Barakat Fellowship

Established by David H. Barakat (ENG 1968) and LaVerne Owen-Barakat in 2013 to support graduate students in the College of Engineering.

• Nayesha Gandotra, Mechanical Engineering
• Orkun Irsoy, Electrical and Computer Engineering

Bradford and Diane Smith Fellowship in Engineering

Established by Bradford L. (ENG 1969) and Diane J. Smith (DC 1971) in 2010 to support doctoral students in the College of Engineering.

• Leia Jiang, Biomedical Engineering
• Shidhartho Roy, Biomedical Engineering

ATK-Nick G. Vlahakis Fellowship

Established in 2003 by the ATK Foundation in honor of Nick G. Vlahakis (ENG 1974), this fund provides support for master's degree candidates in mechanical engineering, electrical and computer engineering, or materials science and engineering, or to students pursuing a joint MBA/B.S. in engineering within the aforementioned departments.

• Holly Chen, Mechanical Engineering
• Zachary Kushnir, Mechanical Engineering
• Junil Min, Mechanical Engineering

Presidential Fellowship

The College of Engineering recognizes high-achieving Ph.D. students with a Presidential Fellowship, covering an entire year of tuition.

• Joel Disu, Biomedical Engineering
• Miaosi Dong, Civil and Environmental Engineering
• Zhixiong Li, Mechanical Engineering
• Catalina Montoya, Biomedical Engineering
• Tejus Surendran, Biomedical Engineering
• Yi Yang, Materials Science Engineering

Wei Shen and Xuehong Zhang Presidential Fellowship

Established by Wei Shen and Xuehong Zhang in 2019 to provide fellowship support for graduate students enrolled in electrical and computer engineering. Wei Shen and Xuehong Zhang are parents of Chen Shen (ENG 2022).

• Artharva Raut, Electrical and Computer Engineering
• Zhaoyi Zhou, Electrical and Computer Engineering

Richard King Mellon Foundation Presidential Fellowship in Energy

Established by the Richard King Mellon Foundation in 2014 to support outstanding graduate students who conduct energy research.

• Ian Martin, Chemical Engineering
• Haoran Ni, Materials Science and Engineering

Ruth Furman Miller and David H. Miller Presidential Fellowship in the Department of Civil and Environmental Engineering

Established by Ruth Furman Miller (MM 1942) through her estate to support graduate students enrolled in the College of Engineering's Department of Civil and Environmental Engineering.

• Maximiliano Larrain Silva, Civil and Environmental Engineering

Thomas and Maria Fok Presidential Fellowship in the Department of Civil and Environmental Engineering

Established by Thomas D.Y. Fok, Ph.D. (ENG 1956) in 2017 to support graduate students enrolled in the Department of Civil and Environmental Engineering.

• Abias Nabimanya, Civil and Environmental Engineering

CyLab Presidential Fellow

CyLab Security and Privacy Institute recognizes high-achieving Ph.D. students pursuing security and/or privacy-related research with a CyLab Presidential Fellowship, covering an entire year of tuition.

• Elijah Bouma-Sims, Software and Societal Systems
• Hao-Ping (Hank) Lee, Human-Computer Interaction
• Terrance Liu, Machine Learning
• Alexandra Nisenoff, Software and Societal Systems
• Hugo Sadok, Computer Science
• Rose Silver, Computer Science
• Taro Tsuchiya, Software and Societal Systems

Heinz Endowments-Lowell Steinbrenner Presidential Graduate Fellowship in Sustainability Science

Established in 2014 through a combination of support from the Heinz Endowments, the Steinbrenner Institute for Environmental Education and Research (SEER) and CMU, this fund is a tribute to Lowell Steinbrenner, a pioneer of environmental education and research, and recognizes outstanding graduate students with exceptional potential to make an impact in sustainability science over the course of their careers.

• Nana Oye Ndaase Djan, Engineering and Public Policy

K&L Gates Presidential Fellowship

Established in 2016 by K&L Gates, LLP to support graduate students whose studies relate to the field of ethics and computational science and technology, and who are enrolled in programs leading to a Ph.D. degree at CMU.

• Che-Yu Lin, Civil and Environmental Engineering

TCS Presidential Fellowship

Established in 2015 by Tata Consultancy Services Limited to support graduate students enrolled at Carnegie Mellon University.

• Mangalam Sahai, Mechanical Engineering

James Sprague Presidential Fellowship

Established by James Sprague (ENG 1909) to provide support to graduate students enrolled in the College of Engineering.

• Hanjiang Hu, Electrical and Computer Engineering

Airports around the world are struggling to keep pace with rising air traffic, and the pressure on air traffic controllers has never been greater. In busy towers, controllers must manage dense, fast-changing traffic on runways and taxiways, while simultaneously juggling unpredictable schedules, variable aircraft behavior, and the constant risk of congestion on the ground.

Traditionally, efforts to improve airside efficiency have focused on optimizing runway assignments, but these decisions do not happen in isolation. A choice that speeds up departures, for example, can unintentionally create cascading effects that lead to bottlenecks on taxiways or increase the likelihood of conflicts between aircraft. Few tools currently capture these interconnected effects or account for the specific operational uncertainties, such as varying taxiing speeds and schedule deviations, that controllers must manage daily.

A new study published in the Journal of Computing in Civil Engineering aims to ease that burden, while increasing airport safety, efficiency, and sustainability. The team introduces a trajectory-based simulation and multi-objective optimization framework designed to help controllers make safer, more efficient runway assignment decisions.

AASTU is a public higher education institution established in 2011 as part of Ethiopia’s strategic vision to advance industrialization, technological innovation, and STEM education.

AASTU is a public higher education institution established in 2011 as part of Ethiopia’s strategic vision to advance industrialization, technological innovation, and STEM education.

Heat behaves in predictable ways: a hot cup of coffee cools, a laptop warms your hands, the sun heats the Earth. But at scales thousands of times smaller than a human hair, those rules begin to break down and scientists are learning how to take advantage of that.

A new study, published in Nature, from researchers at Carnegie Mellon University, in collaboration with Stanford University and Purdue University, shows that heat can be manipulated far more powerfully than previously demonstrated using carefully engineered metamaterials. The work offers one of the clearest experimental confirmations yet that heat transfer can be actively designed and enhanced.

At the core of the discovery is a phenomenon called near-field radiative heat transfer. When two objects are brought extremely close together—just a few hundred nanometers apart—heat doesn’t simply radiate away in the usual sense. Instead, it can tunnel across the gap through electromagnetic waves, dramatically increasing how much energy flows between them.

Scientists have known about this effect for years, but they hadn’t been able to show experimentally, until now, how to push it even further using artificial structures. That’s where metamaterials come in.

“Unlike conventional materials, metamaterials are built with tiny, repeating patterns that interact with energy in precise ways,” said Sheng Shen, a professor of mechanical engineering at Carnegie Mellon University and senior author of the study. “We patterned microscopic gold structures onto thin membranes and positioned them face-to-face across a nanoscale gap. This increased heat transfer by as much as four times compared to similar setups without metamaterials, which is far beyond what traditional physics would predict at larger distances.”

What makes the finding especially compelling is how it works.

“Rather than simply adding more pathways for heat, the gold structures interact with naturally occurring energy waves in the material, known as surface phonon polaritons, creating a resonance effect,” said Zexiao Wang, a Ph.D. student in Shen’s research group and co-first author of the study. “These coupled vibrations allow energy to move more freely and efficiently across the gap.”

“It’s a cooperative effect,” Shen said. “The structures and the material amplify each other.”

Beyond the lab, the implications could be significant. As electronic devices shrink and computing power grows, managing heat has become one of the biggest engineering challenges. The ability to precisely control how heat flows could lead to new cooling strategies for chips and high-performance systems.

There are also implications for energy. Technologies that convert heat into electricity, such as thermophotovoltaic systems, rely on efficiently moving thermal radiation. Enhancing that process could make them significantly more practical.

In sensing technologies, like infrared, stronger and more controllable heat signals could improve detection capabilities in fields ranging from environmental monitoring to national security.

For now, the work remains at the nanoscale, conducted in carefully controlled laboratory conditions, but this marks an important shift from theory to demonstration.

“If heat can be engineered with the same precision as electricity or light, it may open the door to a new class of technologies built not just to withstand heat, but to harness it,” Shen said.

This work is supported by the Defense Threat Reduction Agency, the National Science Foundation, and the Air Force Office of Scientific Research. Sheng Shen and Shanhui Fan are the corresponding authors. Zexiao Wang, Renwen Yu, and Hakan Salihoglu contributed equally to this work.

The gut plays a major role in stress levels in the human body. Often called the “second brain,” the gut constantly talks to the brain, influencing mood and regulating stress hormones like cortisol. Doctors know that persistently high levels of cortisol negatively affect the human body. What they haven’t figured out is a precise way to control it, until now.

Researchers from Carnegie Mellon University aim to develop a swallowable smart pill that temporarily lives in the gut and reduces stress hormones by precisely stimulating gut nerves, all without surgery or drugs. The team recently received funding through the Defense Advanced Research Projects Agency (DARPA) to support its CoasterChase program.

The technology, called GutHarmony, could temporarily change how gut nerves function in order to reduce stress in the body. Once swallowed, the pill dissolves in the lower portion of the small intestine, releasing a tiny, soft, stent-like device that remains in place for a few days. Once there, it can sense chemical signals linked to stress and deliver tiny, targeted stimulations to modulate activity in gut nerves and hormone-releasing cells.

“If high levels of cortisol are detected, the device will direct your adrenal glands to ease off production, lowering stress levels in the body,” says Pulkit Grover, the principal investigator on the project, and a professor of electrical and computer engineering, biomedical engineering, and CMU’s Neuroscience Institute.

The first fully ingestible closed-loop neuromodulation system, GutHarmony would continuously sense chemical levels and would only adjust electrical stimulations when high levels of cortisol are detected. Whereas an open-loop neuromodulation system lacks the detection feature and will continuously release preprogrammed stimulation, no matter the chemical levels.

This spring, Carnegie Mellon University’s College of Engineering awarded professorships to four esteemed faculty members. They will be honored at a formal ceremony in fall 2026. Congratulations to the four recipients, listed below.

Sarah Bergbreiter

Dan and Karen Swanson Endowed Professor

Bergbreiter is a professor in the Department of Mechanical Engineering. Her research focuses on the challenges of engineering robotic systems down to sub-millimeter size scales. She works on small mobile robots and microfabrication in support of larger robotic systems. Bergbreiter is the inaugural recipient of the Dan and Karen Swanson Endowed Professorship.

Maysam Chamanzar

Howard M. Wilkoff Professorship of Electrical and Computer Engineering

Chamanzar is a professor of electrical and computer engineering. He has dedicated his research to understanding the brain and developing novel tools and techniques to better understand the nervous system. Chamanzar has pioneered research in implantable neural interfaces and non-invasive virtual ultrasonically sculpted optics.

Adam Feinberg

Robert Mehrabian Professor of Biomedical Engineering and Materials Science and Engineering

Feinberg is a professor in the Departments of Biomedical Engineering and Materials Science and Engineering. His research focuses on engineering extracellular matrix protein scaffolds using advanced biomanufacturing and 3D bioprinting approaches for multiple applications including cancer models, regenerative scaffolds, skeletal muscle and cardiac muscle tissue engineering.

Carlee Joe-Wong

Sense of Wonder Group Professorship of Electrical and Computer Engineering in AI Systems

Joe-Wong is a professor in the Department of Electrical and Computer Engineering. She focuses on the mathematical aspects of computer and information networks and systems, with an emphasis on economic and incentive considerations. Joe-Wong is particularly interested in applying theoretical insights to practical system deployments.

A team of researchers from Carnegie Mellon University, in collaboration with Cleveland Clinic’s Cardiovascular Innovation Research Center, has developed an artificial intelligence (AI) system capable of interpreting some of the most complex heart scans in medicine, cardiac magnetic resonance imaging (MRI), without the need for manually labeled training data.

The novel system, called CMR-CLIP, is designed to interpret cardiac MRI scans by connecting moving images of the heart with corresponding clinical radiology reports. In testing, it significantly outperformed general-purpose AI models, in some cases by more than 35%. The system also showed strong potential for improving cardiac imaging analysis, case retrieval and clinical decision support.

“This work demonstrates that domain-specific foundation models can significantly outperform general-purpose AI systems in specialized clinical applications,” said Ding Zhao, associate professor mechanical engineering and co-principal investigator on the study. “By designing models that reflect the structure and complexity of cardiac MRI data, rather than adapting generic image models, we can unlock new levels of performance and clinical utility.”

David Chen of the Cleveland Clinic, a co-principal investigator on the project, emphasized the clinical implications of the work. “Cardiac MRI interpretation is highly specialized and time intensive. Systems like CMR-CLIP have the potential to support clinicians through automated screening, and interpretation support, particularly in settings where expert readers are limited. Such reader assistant tools are critical to improving patient access to this powerful diagnostic technology.”

Carnegie Mellon University Africa celebrated its 13th graduation ceremony on May 15, honoring students from across the continent. The graduates received degrees from the College of Engineering’s master’s of science programs in electrical and computer engineering, information technology, and engineering artificial intelligence. With the graduation of the Class of 2026, CMU-Africa reached an important milestone: 1,000 alumni.

The keynote address was delivered by Iyinoluwa Aboyeji. Aboyeji is a founding partner of Future Africa, Africa’s largest seed stage investor. He has co-founded two of Africa's seven unicorn companies: Andela and Flutterwave. Aboyeji’s remarks focused on what is beneath the surface; it carried through the theme of “unseen and seen.” He offered three pieces of advice to graduates:

• Have the courage to seek and speak the truth. “Pursue truth, and when you find it, share it—not to prove your intelligence, but because a world without objective truth is dangerous.”
• Have hope. “The curse of knowledge is cynicism, particularly when it is based purely on what we can see.”
• Have purpose anchored by love.

He ended his remarks by singing a song from his Yoruba culture that speaks to the chasm between the seen and the unseen.

The human heart does more than beat, it vibrates. This hidden language of motion marks the precise opening and closing of valves, the subtle mechanics of life itself. Measuring these micro-cardiac movements requires specialized sensors placed directly on the chest, typically in a medical setting. Carnegie Mellon researchers have now shown that regular earbuds can be transformed into heart-vibration sensors that measure detailed heart valve activity with almost as much accuracy as chest-mounted medical devices.

The researchers repurposed the sensors already engineered into standard hearables by transforming the built-in speaker, the only transducer common to these devices, to act as an acoustic sensor that captures heart sounds at the ear. The system then uses these signals to reconstruct subtle seismocardiography (SCG) and gyrocardiography (GCG) waveforms to extract the timing of key micro-cardiac events.

The team presented their findings at the 2026 Association of Computing Machinery Conference on Human Factors in Computing Systems.

Carnegie Mellon has a strong cycling culture, with many students, faculty, and staff biking to campus or simply riding around Pittsburgh for exercise and recreation. In recent years, the university has invested in making campus more accessible and safer for cyclists and pedestrians alike with new policies, maps and bike paths, infrastructure, and dismount zones. Still, for some students, something core was missing.

For Kenedy Sánchez and Hosea Santiago-Cruz, that “something” missing was community. They founded the Tartan Bike Project (TBP) at CMU to change that.

The two Ph.D. researchers in the Department of Civil and Environmental Engineering (CEE) are members of the same lab and share an advisor: Greg Lowry, department head and professor of civil and environmental engineering. As friends and lab mates, they both discovered that the other was an avid cyclist and had been involved in student-led bike co-ops during their undergraduate years​​—Sánchez at University of Texas at Austin and Santiago-Cruz at the University of Puerto Rico at Mayagüez.

As climate change brings heavier rainfall, rising temperatures, and increased flooding to the Northeast, communities are facing growing strain on infrastructure that wasn’t designed for these extreme conditions. In Allegheny County, home to Carnegie Mellon University and the city of Pittsburgh, steep hillsides, aging stormwater infrastructure, and more than 100 municipalities intersect, making these challenges especially urgent, yet increasingly complex to solve.

With support from the National Science Foundation’s Regional Resilience Innovation Incubator (R2I2) program, civil and environmental researchers at Carnegie Mellon are leading a new effort to help the communities in their own backyard respond. The project brings together engineers, scientists, educators, and local partners to develop a county-wide climate adaptation strategy to scale “green infrastructure,” or nature-based solutions that work with the environment to mitigate climate impacts. 

Green infrastructure encompasses systems like rain gardens, native meadows, tree canopies, and bioswales that absorb and filter stormwater, reduce urban heat, and improve water quality. They can be implemented as an alternative to traditional “gray infrastructure,” or engineered systems like pipes, sewers, and treatment plants that are designed to move water quickly, but often at a high financial and environmental cost. Despite its promise, green infrastructure has been difficult to implement at scale due to a range of bureaucratic barriers from limited funding to maintenance capacity.

“The city of Pittsburgh, led by ALCOSAN, is currently increasing their wastewater treatment plant capacity while also building massive tunnels to store our combined sewer flows,” said David Rounce, assistant professor of civil and environmental engineering. “Those multi-billion-dollar gray infrastructure problems should prevent that combined sewer flow from discharging into our rivers. But we also have to recognize the value of green infrastructure at smaller scales. It can help reduce the burden on this new system, especially as precipitation gets worse in the future, and provide numerous co-benefits.”

Carnegie Mellon University has named six faculty members as University Professors, recognizing their exceptional contributions to research, education, and interdisciplinary collaboration. Linda Argote, Jon Cagan, Rebecca Nugent, Roni Rosenfeld, Richard Scheines, and Kannan Srinivasan join a distinguished group of scholars whose work spans disciplines and drives impact across fields.

The University Professor designation is the highest distinction a faculty member can receive at Carnegie Mellon, awarded to individuals whose research, teaching and leadership transcend traditional academic boundaries. From advancing how organizations learn and how products are designed to shaping data science education, language technologies and decision-making, these faculty members are influencing both scholarship and real-world practice.

Together, their work reflects Carnegie Mellon’s commitment to addressing complex challenges through cross-disciplinary innovation, with applications that extend from classrooms and laboratories to industry and society.

Jon Cagan is the David and Susan Coulter Head and George Tallman and Florence Barrett Ladd Professor of the Department of Mechanical Engineering in the College of Engineering, and a leader in design research and product development. His work spans engineering, design, and innovation, with an emphasis on how ideas move from concept to implementation.

Cagan’s research focuses on computational design methods, including the use of artificial intelligence to support creativity and decision-making in engineering. He develops tools and frameworks that help teams explore design spaces, generate novel concepts and make more informed choices during product development.

A longtime educator and collaborator, Cagan has played a central role in building interdisciplinary efforts that connect engineering with business and design. He co-founded and co-directed the university’s Integrated Innovation Institute. His research and leadership have shaped how organizations approach innovation, influencing practices that balance user needs, technical feasibility and application constraints.

Read about all of the new University Professors.

On a stage designed to mimic Shark Tank, three engineering seniors stepped forward with a deceptively simple idea: what if your tennis racket could coach you?

At the Forge to Field AI Pitch Competition, a national showcase for scale-ready sports tech, startups competed for slices of a $1.75 million prize pool, including up to $1 million in cloud credits from Amazon Web Services. The judging panel had heavy hitters, anchored by billionaire entrepreneurs Mark Cuban and Ed Stack, the executive chairman and chief merchant of DICK’S Sporting Goods.

Geronimo Carom, Mario Cruz, and David Hershenson, all seniors in electrical and computer engineering, presented their startup, ServeSense. Their pitch: a hardware-software system embedding a compact sensor directly into a tennis racket, capturing high-resolution swing data in real time.

On a stage designed to mimic Shark Tank, three engineering seniors stepped forward with a deceptively simple idea: what if your tennis racket could coach you?

At the Forge to Field AI Pitch Competition, a national showcase for scale-ready sports tech, startups competed for slices of a $1.75 million prize pool, including up to $1 million in cloud credits from Amazon Web Services. The judging panel had heavy hitters, anchored by billionaire entrepreneurs Mark Cuban and Ed Stack, the executive chairman and chief merchant of DICK’S Sporting Goods.

Geronimo Carom, Mario Cruz, and David Hershenson, all seniors in electrical and computer engineering, presented their startup, ServeSense. Their pitch: a hardware-software system embedding a compact sensor directly into a tennis racket, capturing high-resolution swing data in real time.

On a stage designed to mimic Shark Tank, three engineering seniors stepped forward with a deceptively simple idea: what if your tennis racket could coach you?

At the Forge to Field AI Pitch Competition, a national showcase for scale-ready sports tech, startups competed for slices of a $1.75 million prize pool, including up to $1 million in cloud credits from Amazon Web Services. The judging panel had heavy hitters, anchored by billionaire entrepreneurs Mark Cuban and Ed Stack, the executive chairman and chief merchant of DICK’S Sporting Goods.

Geronimo Carom, Mario Cruz, and David Hershenson, all seniors in electrical and computer engineering, presented their startup, ServeSense. Their pitch: a hardware-software system embedding a compact sensor directly into a tennis racket, capturing high-resolution swing data in real time.

On a stage designed to mimic Shark Tank, three engineering seniors stepped forward with a deceptively simple idea: what if your tennis racket could coach you?

At the Forge to Field AI Pitch Competition, a national showcase for scale-ready sports tech, startups competed for slices of a $1.75 million prize pool, including up to $1 million in cloud credits from Amazon Web Services. The judging panel had heavy hitters, anchored by billionaire entrepreneurs Mark Cuban and Ed Stack, the executive chairman and chief merchant of DICK’S Sporting Goods.

Geronimo Carom, Mario Cruz, and David Hershenson, all seniors in electrical and computer engineering, presented their startup, ServeSense. Their pitch: a hardware-software system embedding a compact sensor directly into a tennis racket, capturing high-resolution swing data in real time.

On a stage designed to mimic Shark Tank, three engineering seniors stepped forward with a deceptively simple idea: what if your tennis racket could coach you?

At the Forge to Field AI Pitch Competition, a national showcase for scale-ready sports tech, startups competed for slices of a $1.75 million prize pool, including up to $1 million in cloud credits from Amazon Web Services. The judging panel had heavy hitters, anchored by billionaire entrepreneurs Mark Cuban and Ed Stack, the executive chairman and chief merchant of DICK’S Sporting Goods.

Geronimo Carom, Mario Cruz, and David Hershenson, all seniors in electrical and computer engineering, presented their startup, ServeSense. Their pitch: a hardware-software system embedding a compact sensor directly into a tennis racket, capturing high-resolution swing data in real time.

Sarah Moses (MSIT ’26) grew up in South Sudan and Kenya where her community, and many others, had limited or no access to electricity. As an engineering student looking back on this experience, she wanted to understand ways to overcome the issues that developers face when trying to build energy infrastructure on the continent. 

Her first step was to dive into the topic of electricity generation. She signed up for the course “Integrated Energy Systems,” taught by Jesse Thornburg, assistant teaching professor and principal investigator in the Energy with AI Lab at CMU-Africa.

“In a class of electrical engineering students, Sarah was the only person pursuing a Master of Science in Information Technology,” Thornburg said. “With her undergraduate background in computer science, she brought a different perspective: viewing large-scale power generation projects through the lens of artificial intelligence (AI).”

Moses homed in on the step-by-step process that developers follow. She saw an opportunity to use AI to lower costs and save time in this process, starting with the prefeasibility study.

“The prefeasibility study is the critical first step developers take to prove the viability of the project and secure funding. Unfortunately, it can take months to years to do a study, and thousands of dollars, even on the low end,” explains Thornburg. “Besides barriers such as the cost of the study and the time it takes, there are also issues related to lack of data or uncertainty about data’s reliability.”

On the eve of Spring Carnival, Burcu Akinci was installed as the Dr. William D. and Nancy W. Strecker Dean of the College of Engineering. Family and friends, faculty and staff, university leadership, students, alumni, and distinguished guests all gathered to celebrate the formal installation of Dean Akinci on Wednesday, April 8, 2026. Akinci is the 16th dean in the college’s history, and the second to hold the Strecker chair.

Akinci thanked the Streckers for their enduring commitment to the College of Engineering and CMU and promised to uphold their legacy during her tenure as dean.

“I am honored to take on this role, and I look forward to what we will build together—not only what is possible, but what truly matters for generations to come,” said Akinci.

Akinci began her service as dean on January 1, 2026. A member of the CMU community for more than 25 years, Akinci previously served as head of the Department of Civil and Environmental Engineering, and was named a University Professor in 2023, the highest designation for faculty at Carnegie Mellon. She also served as associate dean for research, driving institutional-level growth by helping to establish the moonshot initiative to cultivate large-scale research centers, developing the college's strategic research direction, and increasing the value of new research awards.

On the eve of Spring Carnival, Burcu Akinci was installed as the Dr. William D. and Nancy W. Strecker Dean of the College of Engineering. Family and friends, faculty and staff, university leadership, students, alumni, and distinguished guests all gathered to celebrate the formal installation of Dean Akinci on Wednesday, April 8, 2026. Akinci is the 16th dean in the college’s history, and the second to hold the Strecker chair.

Akinci thanked the Streckers for their enduring commitment to the College of Engineering and CMU and promised to uphold their legacy during her tenure as dean.

“I am honored to take on this role, and I look forward to what we will build together—not only what is possible, but what truly matters for generations to come,” said Akinci.

Akinci began her service as dean on January 1, 2026. A member of the CMU community for more than 25 years, Akinci previously served as head of the Department of Civil and Environmental Engineering, and was named a University Professor in 2023, the highest designation for faculty at Carnegie Mellon. She also served as associate dean for research, driving institutional-level growth by helping to establish the moonshot initiative to cultivate large-scale research centers, developing the college's strategic research direction, and increasing the value of new research awards.

In Chris McComb’s Mechanics II: 3D Design course, artificial intelligence isn’t the expert or a shortcut to producing perfectly polished designs. Instead, AI plays a far more interesting role. It is forcing students to think more critically and, in the process, become the experts themselves.

“In education, a lot of people are finding ways to turn AI into a tutor,” said McComb, associate professor of mechanical engineering and director of the Human + AI Design Initiative. “But it’s not capable enough to handle the nuance of specialized engineering topics yet. So, instead of asking AI to teach my students, I asked my students to teach AI.”

Building on the “see one, do one, teach one” learning paradigm—which has demonstrated that teaching material to others enhances information processing, performance, and motivation—McComb and MIIPS student Giovannia Natasha prompted Microsoft CoPilot to function as a tutee in McComb’s14-week mechanical engineering course. Throughout the semester, students interacted with the genAI tool on eight homework assignments, using pre-engineered prompts that instructed the AI to make specific mistakes and to act like a novice student. Each prompt was given to the students in Indonesian so that they were unaware of what mistakes to lookout for.

Students in the Spring 2025 course who used AI as a tutee significantly outperformed students from the previous semester in three of the four major concept areas: predicting deformation, predicting failure, and understanding the influence of material properties. Performance on the fourth concept, predicting the location of failure, remained consistent with the prior semester.

Artificial intelligence (AI) is poised to drive the next industrial revolution. Large language models alone attract millions of users weekly and process billions of prompts each day. Despite its proven utility across virtually every industry, the data centers powering these systems consume enormous amounts of electricity, placing considerable pressure on the electric grid.

As AI adoption accelerates, data center power consumption is projected to rise significantly. Meeting that demand by building new data centers is costly, both financially and in navigating regulatory requirements. At the same time, the rapid growth of AI computing is creating new challenges for energy providers trying to maintain grid stability.

Researchers at Carnegie Mellon University (CMU) are partnering with Bosch Research (Pittsburgh, PA) to explore how AI data centers can operate more efficiently by coordinating computing workloads with energy availability. Their project focuses on jointly optimizing AI job scheduling and energy use to reduce grid strain and increase renewable energy utilization.

“The world is going through a major AI revolution in regard to large models that are changing our daily lives,” says Guannan Qu, assistant professor of electrical and computer engineering at CMU. “These large models must run in data centers, which consume substantial energy. This, in turn, only feeds the interest to develop even more data centers to support additional models.”

Large AI workloads can place significant strain on electrical infrastructure. When major AI training jobs start or end, abrupt changes in energy demand can cause fluctuations that affect residents by disrupting the energy grid.

“AI labs run large training workloads, which causes frequency fluctuations on the grid because those workloads will use a lot of energy but then suddenly will use much less energy,” says Gauri Joshi, associate professor of electrical and computer engineering at CMU. “Energy providers occasionally need to bring in additional sources of energy, such as spinning up generators, to support increased energy demand. This can affect people living near data centers, raising their electricity bills. Reports of these cases are appearing in many states that have data centers, including Pennsylvania.”

To address these challenges, the research team is investigating how AI workloads can be scheduled more intelligently to work around peak energy demands. Instead of running computing tasks whenever servers are free, data centers could align workloads with periods when renewable energy is abundant.

For thousands of years, salmon have sustained communities along Alaska’s Yukon River, not only as a food source, but also as a cornerstone of culture and tradition. Today, however, those salmon populations are declining, and researchers are examining if current policies that are meant to protect them are working as intended, for both the ecosystems and the people who depend on them.

A new study from Carnegie Mellon’s Department of Engineering and Public Policy evaluated how well the Alaska Department of Fish and Game (ADF&G) follows policies designed to promote both ecological and social sustainability in its management of salmon fisheries. By combining historical data analysis and interviews with traditional subsistence users, the team assessed if management decisions align with legal mandates and whether those decisions actually produce sustainable outcomes.

Fisheries are often described as social-ecological systems, meaning environmental conditions and human well-being are closely linked, and in the Yukon River region, that connection is especially strong. Salmon have supported Alaska Native communities for at least 11,500 years, yet populations have experienced decades of decline attributed to pressures like warming oceans, changing river conditions, and harvest impacts across multiple regions and jurisdictions.

“Traditional users of the Yukon River have engaged in reciprocal relationships with salmon since time immemorial,” said Sabrina Curtis, Ph.D. student studying engineering and public policy and lead author of the paper. “But today, they need help to balance systems of management with globalization, industry, and culture.”

This year is the fifth year of Carnegie Mellon University recognizing Tartans on the Rise, a group of alumni who have graduated within the past 10 years and who are already having an outstanding impact in their fields and communities through leadership, innovation, and career achievements. Four out of this year’s 16 Tartans on the Rise honorees are graduates of the College of Engineering.

David Ajoku (MechE 2021)

Founder and CEO, Aware.ai

When David Ajoku lost his mother, he was inspired to start Aware.ai—an artificial intelligence-driven platform designed to reimagine pregnancy and post-partum care by turning emotional moments into real support and care for new and expecting moms.

“My mom used to tell me, ‘You want to go to space, but there are too many problems here on Earth,’” he says. “I realized that while I loved technical challenges, I was most motivated by deeply human problems. And in honor of my mom, that’s what led me to maternal health.”

Reshmi Ghosh (CEE 2017, 2021; EPP 2020)

Senior Applied Scientist and Technical Lead, Microsoft

As part of the MSAI Responsible AI team, Reshmi Ghosh pioneered Azure Prompt Shields, a machine-learning model supporting safe and reliable prompting.

“Security and safety risks around generative AI systems for search and agents are continuously evolving,” she says. “We develop safety filters to detect and prevent data exfiltration attempts, which happen when malicious instructions are hidden in a third-party document that’s uploaded with a prompt.”

Reshmi’s job is among the most coveted in the AI space. She joined Microsoft as one of about 20 members of the company’s annual AI Responsibility incubator, selected from a pool of almost 20,000 applicants.

Susana Lau (INI 2015)

Founder and CEO, EtyaLab

Susana Lau’s firm, EtyaLab, specializes in digital transformation through mobile applications, web platforms, websites, e-commerce systems, and tailor-made digital products. In the past 10 years, she grew the company to a team of 20 staff. Today, it’s a trusted name in technology in Panama and growing across Latin America.

"I grew up seeing my parents being business people on a small scale, then at school my vision to make something of myself met the Silicon Valley/startup mindset. That put me where I am today, and leading by example especially for younger generations,” she says.

Sakshi Mishra (ESTP 2015)

Co-founder, Verber Studio

Sakshi Mishra isn't just applying artificial intelligence—she is architecting the infrastructure that controls it. With her new venture, Sakshi is tackling the "orchestration" problem in generative AI. She is the co-founder of Verber Studio, a creative operating system designed to close the gap between raw AI potential and reliable business results.

“We’re moving into an era where the cost of creation has hit zero, but the cost of management has skyrocketed,” she says. “The new barrier isn't building a product or generating assets; it's distributing the narrative. Verber Studio provides the ‘orchestration layer’ that allows teams to scale their story without losing their soul.”

***

We’re so proud of all our Tartans on the Rise, and we can’t wait to see what they do next! Learn more about this year’s Tartans on the Rise.

This year is the fifth year of Carnegie Mellon University recognizing Tartans on the Rise, a group of alumni who have graduated within the past 10 years and who are already having an outstanding impact in their fields and communities through leadership, innovation, and career achievements. Four out of this year’s 16 Tartans on the Rise honorees are graduates of the College of Engineering.

David Ajoku (MechE 2021)

Founder and CEO, Aware.ai

When David Ajoku lost his mother, he was inspired to start Aware.ai—an artificial intelligence-driven platform designed to reimagine pregnancy and post-partum care by turning emotional moments into real support and care for new and expecting moms.

“My mom used to tell me, ‘You want to go to space, but there are too many problems here on Earth,’” he says. “I realized that while I loved technical challenges, I was most motivated by deeply human problems. And in honor of my mom, that’s what led me to maternal health.”

Reshmi Ghosh (CEE 2017, 2021; EPP 2020)

Senior Applied Scientist and Technical Lead, Microsoft

As part of the MSAI Responsible AI team, Reshmi Ghosh pioneered Azure Prompt Shields, a machine-learning model supporting safe and reliable prompting.

“Security and safety risks around generative AI systems for search and agents are continuously evolving,” she says. “We develop safety filters to detect and prevent data exfiltration attempts, which happen when malicious instructions are hidden in a third-party document that’s uploaded with a prompt.”

Reshmi’s job is among the most coveted in the AI space. She joined Microsoft as one of about 20 members of the company’s annual AI Responsibility incubator, selected from a pool of almost 20,000 applicants.

Susana Lau (INI 2015)

Founder and CEO, EtyaLab

Susana Lau’s firm, EtyaLab, specializes in digital transformation through mobile applications, web platforms, websites, e-commerce systems, and tailor-made digital products. In the past 10 years, she grew the company to a team of 20 staff. Today, it’s a trusted name in technology in Panama and growing across Latin America.

"I grew up seeing my parents being business people on a small scale, then at school my vision to make something of myself met the Silicon Valley/startup mindset. That put me where I am today, and leading by example especially for younger generations,” she says.

Sakshi Mishra (ESTP 2015)

Co-founder, Verber Studio

Sakshi Mishra isn't just applying artificial intelligence—she is architecting the infrastructure that controls it. With her new venture, Sakshi is tackling the "orchestration" problem in generative AI. She is the co-founder of Verber Studio, a creative operating system designed to close the gap between raw AI potential and reliable business results.

“We’re moving into an era where the cost of creation has hit zero, but the cost of management has skyrocketed,” she says. “The new barrier isn't building a product or generating assets; it's distributing the narrative. Verber Studio provides the ‘orchestration layer’ that allows teams to scale their story without losing their soul.”

***

We’re so proud of all our Tartans on the Rise, and we can’t wait to see what they do next! Learn more about this year’s Tartans on the Rise.

This year is the fifth year of Carnegie Mellon University recognizing Tartans on the Rise, a group of alumni who have graduated within the past 10 years and who are already having an outstanding impact in their fields and communities through leadership, innovation, and career achievements. Four out of this year’s 16 Tartans on the Rise honorees are graduates of the College of Engineering.

David Ajoku (MechE 2021)

Founder and CEO, Aware.ai

When David Ajoku lost his mother, he was inspired to start Aware.ai—an artificial intelligence-driven platform designed to reimagine pregnancy and post-partum care by turning emotional moments into real support and care for new and expecting moms.

“My mom used to tell me, ‘You want to go to space, but there are too many problems here on Earth,’” he says. “I realized that while I loved technical challenges, I was most motivated by deeply human problems. And in honor of my mom, that’s what led me to maternal health.”

Reshmi Ghosh (CEE 2017, 2021; EPP 2020)

Senior Applied Scientist and Technical Lead, Microsoft

As part of the MSAI Responsible AI team, Reshmi Ghosh pioneered Azure Prompt Shields, a machine-learning model supporting safe and reliable prompting.

“Security and safety risks around generative AI systems for search and agents are continuously evolving,” she says. “We develop safety filters to detect and prevent data exfiltration attempts, which happen when malicious instructions are hidden in a third-party document that’s uploaded with a prompt.”

Reshmi’s job is among the most coveted in the AI space. She joined Microsoft as one of about 20 members of the company’s annual AI Responsibility incubator, selected from a pool of almost 20,000 applicants.

Susana Lau (INI 2015)

Founder and CEO, EtyaLab

Susana Lau’s firm, EtyaLab, specializes in digital transformation through mobile applications, web platforms, websites, e-commerce systems, and tailor-made digital products. In the past 10 years, she grew the company to a team of 20 staff. Today, it’s a trusted name in technology in Panama and growing across Latin America.

"I grew up seeing my parents being business people on a small scale, then at school my vision to make something of myself met the Silicon Valley/startup mindset. That put me where I am today, and leading by example especially for younger generations,” she says.

Sakshi Mishra (ESTP 2015)

Co-founder, Verber Studio

Sakshi Mishra isn't just applying artificial intelligence—she is architecting the infrastructure that controls it. With her new venture, Sakshi is tackling the "orchestration" problem in generative AI. She is the co-founder of Verber Studio, a creative operating system designed to close the gap between raw AI potential and reliable business results.

“We’re moving into an era where the cost of creation has hit zero, but the cost of management has skyrocketed,” she says. “The new barrier isn't building a product or generating assets; it's distributing the narrative. Verber Studio provides the ‘orchestration layer’ that allows teams to scale their story without losing their soul.”

***

We’re so proud of all our Tartans on the Rise, and we can’t wait to see what they do next! Learn more about this year’s Tartans on the Rise.

This year is the fifth year of Carnegie Mellon University recognizing Tartans on the Rise, a group of alumni who have graduated within the past 10 years and who are already having an outstanding impact in their fields and communities through leadership, innovation, and career achievements. Four out of this year’s 16 Tartans on the Rise honorees are graduates of the College of Engineering.

David Ajoku (MechE 2021)

Founder and CEO, Aware.ai

When David Ajoku lost his mother, he was inspired to start Aware.ai—an artificial intelligence-driven platform designed to reimagine pregnancy and post-partum care by turning emotional moments into real support and care for new and expecting moms.

“My mom used to tell me, ‘You want to go to space, but there are too many problems here on Earth,’” he says. “I realized that while I loved technical challenges, I was most motivated by deeply human problems. And in honor of my mom, that’s what led me to maternal health.”

Reshmi Ghosh (CEE 2017, 2021; EPP 2020)

Senior Applied Scientist and Technical Lead, Microsoft

As part of the MSAI Responsible AI team, Reshmi Ghosh pioneered Azure Prompt Shields, a machine-learning model supporting safe and reliable prompting.

“Security and safety risks around generative AI systems for search and agents are continuously evolving,” she says. “We develop safety filters to detect and prevent data exfiltration attempts, which happen when malicious instructions are hidden in a third-party document that’s uploaded with a prompt.”

Reshmi’s job is among the most coveted in the AI space. She joined Microsoft as one of about 20 members of the company’s annual AI Responsibility incubator, selected from a pool of almost 20,000 applicants.

Susana Lau (INI 2015)

Founder and CEO, EtyaLab

Susana Lau’s firm, EtyaLab, specializes in digital transformation through mobile applications, web platforms, websites, e-commerce systems, and tailor-made digital products. In the past 10 years, she grew the company to a team of 20 staff. Today, it’s a trusted name in technology in Panama and growing across Latin America.

"I grew up seeing my parents being business people on a small scale, then at school my vision to make something of myself met the Silicon Valley/startup mindset. That put me where I am today, and leading by example especially for younger generations,” she says.

Sakshi Mishra (ESTP 2015)

Co-founder, Verber Studio

Sakshi Mishra isn't just applying artificial intelligence—she is architecting the infrastructure that controls it. With her new venture, Sakshi is tackling the "orchestration" problem in generative AI. She is the co-founder of Verber Studio, a creative operating system designed to close the gap between raw AI potential and reliable business results.

“We’re moving into an era where the cost of creation has hit zero, but the cost of management has skyrocketed,” she says. “The new barrier isn't building a product or generating assets; it's distributing the narrative. Verber Studio provides the ‘orchestration layer’ that allows teams to scale their story without losing their soul.”

***

We’re so proud of all our Tartans on the Rise, and we can’t wait to see what they do next! Learn more about this year’s Tartans on the Rise.

In season nine of Rethink the Rink, 20 students from across Carnegie Mellon University competed in teams of four to design groundbreaking hockey goalie chest protector prototypes with guidance from experts at Covestro, a world-leading supplier of high-tech polymer materials, the Pittsburgh Penguins professional hockey team, and Bauer Hockey, the world’s leading hockey equipment manufacturer.

Students worked over the course of one week to solve issues associated with goalie chest protectors, including impact absorption, mobility, and functionality.

In honor of the nation’s 250^th Anniversary, the U.S. Department of Transportation plans to deploy self-driving shuttle services in Washington DC this summer. As a precursor to the public launch, in January, the US DOT arranged for federal and local government and transportation officials to take test rides in an autonomous shuttle along a two-mile stretch between Navy Yard and Union Station in Washington DC. Researchers from Carnegie Mellon University’s Safety21, a USDOT National University Transportation Center (UTC), were an integral part of this pilot deployment to validate and ensure safety during testing and operations.

The Carnegie Mellon team, led by Raj Rajkumar, the director of Safety21 and professor of electrical and computer engineering, collaborated with US DOT and Beep, Inc., an autonomous mobility company, on a pilot program for autonomous public shuttles. During the DC test rides, the researchers gathered data from the vehicle’s sensors. CMU analyses and recommendations are helping inform how the shuttle bus will navigate safely and make intelligent, real-time decisions in a variety of traffic situations.

The shuttle demonstrations coincided with the Transportation Research Board (TRB) Annual Meeting, which was held on January 11–15, 2026 in the District of Columbia. Thousands of transportation professionals, including policymakers, convened at TRB to discuss advances in all modes of transportation. The deployment of autonomous vehicles (AVs), transportation corridors for AVs, and infrastructural support for AVs were emphasized.

During the TRB meeting, in a panel discussion, titled the “US DOT Innovation Agenda,” US DOT leaders underscored the Trump administration’s priorities to advance the safety and American leadership in automated vehicles, among other technologies.

These priorities align with the goals and mission of CMU’s Safety21. Focusing on autonomous vehicle safety and connected infrastructure, the center addresses challenges by collaborating with government, industry, and community groups on research, development, and deployment (R&D&D) projects.

Rajkumar is glad that Safety21’s collaborative model has been recognized nationally for its success in driving innovation and economic impact, while addressing real-world transportation problems.

The test rides in DC provided local and national officials, including Seval Oz, US DOT senior advisor, Office of the Assistant Secretary for Research and Technology at US DOT, the opportunity to experience first-hand in the nation’s capital a new mode of public transportation that’s emerging across the country.

While the deployment of robotaxis and AV shuttles is dialing up in some cities, AV deployment across the U.S. is sporadic for a variety of reasons including safety concerns, non-uniform regulations, deployment costs, scaling considerations, mapping needs, and environmental challenges like weather conditions.

During the DC test rides, the shuttle drove autonomously for most of its runs; however (as required by DC law) a safety driver with a commercial driver’s license was always behind the steering wheel ready to take over if necessary.

“Since pioneering autonomous vehicle technology in 1984, CMU has helped shape the trajectory of this highly impactful field,” says Rajkumar. “The deployment of this AV shuttle reflects the next chapter in that legacy—moving innovation from research to real-world operation in ways that inform national policy and deployment. By serving as a proving ground for safe, scalable systems, we’re helping ensure the United States remains the global leader in autonomous mobility.”

Soon after the AV shuttle deployment, The Federal Highway Administration (FHWA) released a Sources Sought notice seeking industry input on a potential AV shuttle demonstration in Washington, DC The proposed demonstration would align with events commemorating America’s 250^th Anniversary in July.

In honor of the nation’s 250^th Anniversary, the U.S. Department of Transportation plans to deploy self-driving shuttle services in Washington DC this summer. As a precursor to the public launch, in January, the US DOT arranged for federal and local government and transportation officials to take test rides in an autonomous shuttle along a two-mile stretch between Navy Yard and Union Station in Washington DC. Researchers from Carnegie Mellon University’s Safety21, a USDOT National University Transportation Center (UTC), were an integral part of this pilot deployment to validate and ensure safety during testing and operations.

The Carnegie Mellon team, led by Raj Rajkumar, the director of Safety21 and professor of electrical and computer engineering, collaborated with US DOT and Beep, Inc., an autonomous mobility company, on a pilot program for autonomous public shuttles. During the DC test rides, the researchers gathered data from the vehicle’s sensors. CMU analyses and recommendations are helping inform how the shuttle bus will navigate safely and make intelligent, real-time decisions in a variety of traffic situations.

The shuttle demonstrations coincided with the Transportation Research Board (TRB) Annual Meeting, which was held on January 11–15, 2026 in the District of Columbia. Thousands of transportation professionals, including policymakers, convened at TRB to discuss advances in all modes of transportation. The deployment of autonomous vehicles (AVs), transportation corridors for AVs, and infrastructural support for AVs were emphasized.

During the TRB meeting, in a panel discussion, titled the “US DOT Innovation Agenda,” US DOT leaders underscored the Trump administration’s priorities to advance the safety and American leadership in automated vehicles, among other technologies.

These priorities align with the goals and mission of CMU’s Safety21. Focusing on autonomous vehicle safety and connected infrastructure, the center addresses challenges by collaborating with government, industry, and community groups on research, development, and deployment (R&D&D) projects.

Rajkumar is glad that Safety21’s collaborative model has been recognized nationally for its success in driving innovation and economic impact, while addressing real-world transportation problems.

The test rides in DC provided local and national officials, including Seval Oz, US DOT senior advisor, Office of the Assistant Secretary for Research and Technology at US DOT, the opportunity to experience first-hand in the nation’s capital a new mode of public transportation that’s emerging across the country.

While the deployment of robotaxis and AV shuttles is dialing up in some cities, AV deployment across the U.S. is sporadic for a variety of reasons including safety concerns, non-uniform regulations, deployment costs, scaling considerations, mapping needs, and environmental challenges like weather conditions.

During the DC test rides, the shuttle drove autonomously for most of its runs; however (as required by DC law) a safety driver with a commercial driver’s license was always behind the steering wheel ready to take over if necessary.

“Since pioneering autonomous vehicle technology in 1984, CMU has helped shape the trajectory of this highly impactful field,” says Rajkumar. “The deployment of this AV shuttle reflects the next chapter in that legacy—moving innovation from research to real-world operation in ways that inform national policy and deployment. By serving as a proving ground for safe, scalable systems, we’re helping ensure the United States remains the global leader in autonomous mobility.”

Soon after the AV shuttle deployment, The Federal Highway Administration (FHWA) released a Sources Sought notice seeking industry input on a potential AV shuttle demonstration in Washington, DC The proposed demonstration would align with events commemorating America’s 250^th Anniversary in July.

In honor of the nation’s 250^th Anniversary, the U.S. Department of Transportation plans to deploy self-driving shuttle services in Washington DC this summer. As a precursor to the public launch, in January, the US DOT arranged for federal and local government and transportation officials to take test rides in an autonomous shuttle along a two-mile stretch between Navy Yard and Union Station in Washington DC. Researchers from Carnegie Mellon University’s Safety21, a USDOT National University Transportation Center (UTC), were an integral part of this pilot deployment to validate and ensure safety during testing and operations.

The Carnegie Mellon team, led by Raj Rajkumar, the director of Safety21 and professor of electrical and computer engineering, collaborated with US DOT and Beep, Inc., an autonomous mobility company, on a pilot program for autonomous public shuttles. During the DC test rides, the researchers gathered data from the vehicle’s sensors. CMU analyses and recommendations are helping inform how the shuttle bus will navigate safely and make intelligent, real-time decisions in a variety of traffic situations.

The shuttle demonstrations coincided with the Transportation Research Board (TRB) Annual Meeting, which was held on January 11–15, 2026 in the District of Columbia. Thousands of transportation professionals, including policymakers, convened at TRB to discuss advances in all modes of transportation. The deployment of autonomous vehicles (AVs), transportation corridors for AVs, and infrastructural support for AVs were emphasized.

During the TRB meeting, in a panel discussion, titled the “US DOT Innovation Agenda,” US DOT leaders underscored the Trump administration’s priorities to advance the safety and American leadership in automated vehicles, among other technologies.

These priorities align with the goals and mission of CMU’s Safety21. Focusing on autonomous vehicle safety and connected infrastructure, the center addresses challenges by collaborating with government, industry, and community groups on research, development, and deployment (R&D&D) projects.

Rajkumar is glad that Safety21’s collaborative model has been recognized nationally for its success in driving innovation and economic impact, while addressing real-world transportation problems.

The test rides in DC provided local and national officials, including Seval Oz, US DOT senior advisor, Office of the Assistant Secretary for Research and Technology at US DOT, the opportunity to experience first-hand in the nation’s capital a new mode of public transportation that’s emerging across the country.

While the deployment of robotaxis and AV shuttles is dialing up in some cities, AV deployment across the U.S. is sporadic for a variety of reasons including safety concerns, non-uniform regulations, deployment costs, scaling considerations, mapping needs, and environmental challenges like weather conditions.

During the DC test rides, the shuttle drove autonomously for most of its runs; however (as required by DC law) a safety driver with a commercial driver’s license was always behind the steering wheel ready to take over if necessary.

“Since pioneering autonomous vehicle technology in 1984, CMU has helped shape the trajectory of this highly impactful field,” says Rajkumar. “The deployment of this AV shuttle reflects the next chapter in that legacy—moving innovation from research to real-world operation in ways that inform national policy and deployment. By serving as a proving ground for safe, scalable systems, we’re helping ensure the United States remains the global leader in autonomous mobility.”

Soon after the AV shuttle deployment, The Federal Highway Administration (FHWA) released a Sources Sought notice seeking industry input on a potential AV shuttle demonstration in Washington, DC The proposed demonstration would align with events commemorating America’s 250^th Anniversary in July.

In honor of the nation’s 250^th Anniversary, the U.S. Department of Transportation plans to deploy self-driving shuttle services in Washington DC this summer. As a precursor to the public launch, in January, the US DOT arranged for federal and local government and transportation officials to take test rides in an autonomous shuttle along a two-mile stretch between Navy Yard and Union Station in Washington DC. Researchers from Carnegie Mellon University’s Safety21, a USDOT National University Transportation Center (UTC), were an integral part of this pilot deployment to validate and ensure safety during testing and operations.

The Carnegie Mellon team, led by Raj Rajkumar, the director of Safety21 and professor of electrical and computer engineering, collaborated with US DOT and Beep, Inc., an autonomous mobility company, on a pilot program for autonomous public shuttles. During the DC test rides, the researchers gathered data from the vehicle’s sensors. CMU analyses and recommendations are helping inform how the shuttle bus will navigate safely and make intelligent, real-time decisions in a variety of traffic situations.

The shuttle demonstrations coincided with the Transportation Research Board (TRB) Annual Meeting, which was held on January 11–15, 2026 in the District of Columbia. Thousands of transportation professionals, including policymakers, convened at TRB to discuss advances in all modes of transportation. The deployment of autonomous vehicles (AVs), transportation corridors for AVs, and infrastructural support for AVs were emphasized.

During the TRB meeting, in a panel discussion, titled the “US DOT Innovation Agenda,” US DOT leaders underscored the Trump administration’s priorities to advance the safety and American leadership in automated vehicles, among other technologies.

These priorities align with the goals and mission of CMU’s Safety21. Focusing on autonomous vehicle safety and connected infrastructure, the center addresses challenges by collaborating with government, industry, and community groups on research, development, and deployment (R&D&D) projects.

Rajkumar is glad that Safety21’s collaborative model has been recognized nationally for its success in driving innovation and economic impact, while addressing real-world transportation problems.

The test rides in DC provided local and national officials, including Seval Oz, US DOT senior advisor, Office of the Assistant Secretary for Research and Technology at US DOT, the opportunity to experience first-hand in the nation’s capital a new mode of public transportation that’s emerging across the country.

While the deployment of robotaxis and AV shuttles is dialing up in some cities, AV deployment across the U.S. is sporadic for a variety of reasons including safety concerns, non-uniform regulations, deployment costs, scaling considerations, mapping needs, and environmental challenges like weather conditions.

During the DC test rides, the shuttle drove autonomously for most of its runs; however (as required by DC law) a safety driver with a commercial driver’s license was always behind the steering wheel ready to take over if necessary.

“Since pioneering autonomous vehicle technology in 1984, CMU has helped shape the trajectory of this highly impactful field,” says Rajkumar. “The deployment of this AV shuttle reflects the next chapter in that legacy—moving innovation from research to real-world operation in ways that inform national policy and deployment. By serving as a proving ground for safe, scalable systems, we’re helping ensure the United States remains the global leader in autonomous mobility.”

Soon after the AV shuttle deployment, The Federal Highway Administration (FHWA) released a Sources Sought notice seeking industry input on a potential AV shuttle demonstration in Washington, DC The proposed demonstration would align with events commemorating America’s 250^th Anniversary in July.

In honor of the nation’s 250^th Anniversary, the U.S. Department of Transportation plans to deploy self-driving shuttle services in Washington DC this summer. As a precursor to the public launch, in January, the US DOT arranged for federal and local government and transportation officials to take test rides in an autonomous shuttle along a two-mile stretch between Navy Yard and Union Station in Washington DC. Researchers from Carnegie Mellon University’s Safety21, a USDOT National University Transportation Center (UTC), were an integral part of this pilot deployment to validate and ensure safety during testing and operations.

The Carnegie Mellon team, led by Raj Rajkumar, the director of Safety21 and professor of electrical and computer engineering, collaborated with US DOT and Beep, Inc., an autonomous mobility company, on a pilot program for autonomous public shuttles. During the DC test rides, the researchers gathered data from the vehicle’s sensors. CMU analyses and recommendations are helping inform how the shuttle bus will navigate safely and make intelligent, real-time decisions in a variety of traffic situations.

The shuttle demonstrations coincided with the Transportation Research Board (TRB) Annual Meeting, which was held on January 11–15, 2026 in the District of Columbia. Thousands of transportation professionals, including policymakers, convened at TRB to discuss advances in all modes of transportation. The deployment of autonomous vehicles (AVs), transportation corridors for AVs, and infrastructural support for AVs were emphasized.

During the TRB meeting, in a panel discussion, titled the “US DOT Innovation Agenda,” US DOT leaders underscored the Trump administration’s priorities to advance the safety and American leadership in automated vehicles, among other technologies.

These priorities align with the goals and mission of CMU’s Safety21. Focusing on autonomous vehicle safety and connected infrastructure, the center addresses challenges by collaborating with government, industry, and community groups on research, development, and deployment (R&D&D) projects.

Rajkumar is glad that Safety21’s collaborative model has been recognized nationally for its success in driving innovation and economic impact, while addressing real-world transportation problems.

The test rides in DC provided local and national officials, including Seval Oz, US DOT senior advisor, Office of the Assistant Secretary for Research and Technology at US DOT, the opportunity to experience first-hand in the nation’s capital a new mode of public transportation that’s emerging across the country.

While the deployment of robotaxis and AV shuttles is dialing up in some cities, AV deployment across the U.S. is sporadic for a variety of reasons including safety concerns, non-uniform regulations, deployment costs, scaling considerations, mapping needs, and environmental challenges like weather conditions.

During the DC test rides, the shuttle drove autonomously for most of its runs; however (as required by DC law) a safety driver with a commercial driver’s license was always behind the steering wheel ready to take over if necessary.

“Since pioneering autonomous vehicle technology in 1984, CMU has helped shape the trajectory of this highly impactful field,” says Rajkumar. “The deployment of this AV shuttle reflects the next chapter in that legacy—moving innovation from research to real-world operation in ways that inform national policy and deployment. By serving as a proving ground for safe, scalable systems, we’re helping ensure the United States remains the global leader in autonomous mobility.”

Soon after the AV shuttle deployment, The Federal Highway Administration (FHWA) released a Sources Sought notice seeking industry input on a potential AV shuttle demonstration in Washington, DC The proposed demonstration would align with events commemorating America’s 250^th Anniversary in July.

In Falls River, Massachusetts, a textile manufacturing company established nearly 200 years ago is championing “Made in the USA” by embracing the advanced manufacturing technology the U.S. needs to regain competitive advantage.

Charlie Merrow, CEO and 8^th generation family member of the Merrow Manufacturing company, is collaborating with Pingbo Tang to optimize his company’s production lines.

“Factories aren’t relics. They’re extensions of the lab,” said Merrow. “When we connect research, universities, commercial problems, and production—we accelerate progress.”

In October 2024, a team of Carnegie Mellon University engineers and scientists led by Tang visited Merrow’s 300,000-square-foot facility to model their production processes with limited data. Their goal was to support business decision-making for using automation to scale up their manufacturing lines. The team visited the factory again in December 2025 to continue integrating human intelligence with artificial intelligence (AI). This was based on the previous work that has already helped the company identify opportunities to achieve a potential three-fold increase in their output of T-shirts they produce for the U.S. military.

Tang, an associate professor of civil and environmental engineering, focuses on human interactions with autonomous machines in airports, nuclear power plants, transportation, and construction systems, as well as manufacturing-related research.

In 2021, Tang received seed funding from Carnegie Mellon’s Manufacturing Futures Institute to study how enhancing human-machine collaboration could reduce waste in the manufacture of customized modular housing components, a process that requires frequent changeovers of equipment and production lines.

His team used digital twin technology to train computers to automatically diagnose human-in-the-loop (HITL) production histories reconstructed from field notes, videos of workers, and control system logs of production lines.

Researchers integrated intuitive human expertise, such as how materials behave and machines perform, with advanced machine learning techniques that used the data derived from actual human interactions. Tang’s team was then able to generate plans for safely and efficiently reconfiguring production lines that could accommodate the production of new products without building new lines.

In 2024, Tang received funding from the Manufacturing PA Innovation program to employ a similar human-machine teaming approach to identify and resolve time and resource waste associated with small orders of customized building products for Module, a sustainable modular home manufacturer, and DMI Companies, which provides ventilation ductwork for commercial and residential buildings.

By collecting waste-generation scenarios from four ductwork and connector production lines operated by workers, the researchers used simulations and data analytics to identify ways to reduce the waste of the costly materials used in making the ductwork.

Compelled to dig deeper, Tang is scrutinizing how human behavior informs AI. “Why is one worker better at a task than another?” he asks. “When we can more proactively observe and capture their historical behavior, we can organize that data and use AI to identify the optimal behavior.”

Tang is also working with DMI Companies to conduct human behavior analysis to determine better methods for training workers on a newly commissioned piece of equipment. Tang and his team analyzed the verbal exchanges between the trainers and users, video capture of their interactions, and biometric data of the participants to find better ways to convey how to set up and use the new equipment.

In this case, researchers are trying to determine which training methods and communication styles are most effective to standardize and optimize how workers can gain new skills.

Can a machine design, adapt, and improve other machines—safely, reliably, and without constant human oversight? Answering this question is at the heart of Yorie Nakahira’s research on next-generation autonomous systems.

Nakahira, assistant professor of electrical and computer engineering, has received a Young Investigator Award from the Japan Science and Technology Agency (JST) for developing a machine that builds autonomous systems.

Adaptation is essential because real-world environments are constantly changing. Robots often operate with limited data, limited memory, and limited computing power, making it unrealistic to train them once and expect safe performance forever.

To address this, Nakahira explores sequential fine-tuning, where systems learn gradually as new information becomes available. This enables continual adaptation rather than reliance on a single, massive training dataset.

However, adaptation introduces its own risks: the model can forget past skills or become overly confident. Nakahira’s work also emphasizes uncertainty awareness—teaching systems to recognize when they are unsure and to act cautiously in those moments.

In a breakthrough that could power next-generation electronics, sensors, and energy storage devices, CMU engineers have developed a fabrication technique that arranges MXene nanosheets, each a million times thinner than a sheet of paper, into complex 3D structures in just a single printing step.

“A 3D arrangement of this 2D nanomaterial can help us reach the performance requirements for miniaturized electronic devices like microsupercapacitors and batteries.” said Rahul Panat, lead author of the research published in Small.

MXenes’ outstanding mechanical strength and superior electrochemical stability have captivated researchers for more than a decade. However, their impressive properties alone are not enough to create high-performance devices. The material’s architecture plays a crucial role by governing how efficiently ions and electrons move through an electrode. Without a carefully designed structure, even the most advanced MXenes can run into bottlenecks and barriers.

Carnegie Mellon University’s standing as a powerhouse in engineering research is underscored by the election of Jonathan Cagan, CMU President Farnam Jahanian, and alumnus Ira J. Pitel to the prestigious National Academy of Engineering’s 2026 class.

Election to the NAE is among the highest professional distinctions accorded to an engineer.

Additive manufacturing has revolutionized manufacturing by enabling customized, cost-effective products with minimal waste. However, with a majority of 3D printers operating on open-loop systems, they are notoriously prone to failure. Minor changes, like adjustments to nozzle size or print speed, can lead to print errors that mechanically weaken the part under production.

Traditionally, manufacturers fix these issues on a case-by-case basis, ultimately “babysitting” the printer to manually adjust parameters and test samples in an effort to figure out what went wrong.

Amir Barati Farimani, associate professor of mechanical engineering, is automating 3D printing with a new large language model that fixes printer errors in real time without the need for any pre-training. The model is printer-agnostic and can be used by a wide range of printers for varying materials.

Looking at a sample of parasite-infected blood, researchers at Carnegie Mellon University noticed the unexpected movement of red blood cells. Due to their simple structure, red blood cells are unable to move on their own. So what was happening to them?

Like someone stealing a car to flee from the police, the parasite Babesia microti uses red blood cells to migrate. The newly discovered phenomenon may be a way for it to hide and escape from white blood cells, which do not typically attack red blood cells.

Looking at a sample of parasite-infected blood, researchers at Carnegie Mellon University noticed the unexpected movement of red blood cells. Due to their simple structure, red blood cells are unable to move on their own. So what was happening to them?

Like someone stealing a car to flee from the police, the parasite Babesia microti uses red blood cells to migrate. The newly discovered phenomenon may be a way for it to hide and escape from white blood cells, which do not typically attack red blood cells.

Looking at a sample of parasite-infected blood, researchers at Carnegie Mellon University noticed the unexpected movement of red blood cells. Due to their simple structure, red blood cells are unable to move on their own. So what was happening to them?

Like someone stealing a car to flee from the police, the parasite Babesia microti uses red blood cells to migrate. The newly discovered phenomenon may be a way for it to hide and escape from white blood cells, which do not typically attack red blood cells.

Looking at a sample of parasite-infected blood, researchers at Carnegie Mellon University noticed the unexpected movement of red blood cells. Due to their simple structure, red blood cells are unable to move on their own. So what was happening to them?

Like someone stealing a car to flee from the police, the parasite Babesia microti uses red blood cells to migrate. The newly discovered phenomenon may be a way for it to hide and escape from white blood cells, which do not typically attack red blood cells.

Carnegie Mellon University’s Erica Fuchs will join leaders from across government, technology, business, and academia to participate in the World Economic Forum Annual Meeting in Davos, Switzerland from January 19-23, 2026.

Every year, the Forum hosts forward-looking forums and panels to address widespread global challenges from economic stability to digital trust to climate resilience. This year’s theme, A Spirit of Dialogue, aims to serve as an impartial platform to exchange ideas, broaden perspectives, and support problem-solving during a period of significant geopolitical and societal change.

Fuchs, director of CMU’s Critical Technology Initiative and professor of engineering and public policy, researches how emerging technologies are developed, commercialized, and manufactured, and the policies governments need to support national competitiveness in those areas. Throughout the week in Davos, she will participate in sessions aligning with her expertise on topics such as intelligent infrastructure, workforce development for advanced manufacturing, industrial policy, and the future of research.

Fuchs will also moderate two sessions. The first, titled “How can governments innovate?,” explores how public institutions can adopt more adaptive and experimental approaches to policymaking. By adapting the approach of product designers, the panelists will consider the use of frontier tools, iterative methods, and future-focused perspectives to create bold and adaptive systems that are ready for tomorrow's challenges.

The second session, “AI for Curricular Value Chains,” examines how artificial intelligence can improve material design, efficiency, transparency, and reuse across global production systems, while at the same time enhancing economic competitiveness and supply chain resiliency. Fuchs will oversee discussion on the applications of AI in chemicals, textiles, and electronics, and considerations of the data standards, infrastructure, and cross-industry collaboration necessary to scale circular manufacturing processes.

Her participation builds on two decades of involvement in national and international discussions on technology policy, including at previous WEF meetings and on WEF committees. In 2012, Fuchs was selected as a World Economic Forum Young Scientist and has been an invited speaker at past WEF events, including the Annual Meeting of the New Champions.

Carnegie Mellon University’s Erica Fuchs will join leaders from across government, technology, business, and academia to participate in the World Economic Forum Annual Meeting in Davos, Switzerland from January 19-23, 2026.

Every year, the Forum hosts forward-looking forums and panels to address widespread global challenges from economic stability to digital trust to climate resilience. This year’s theme, A Spirit of Dialogue, aims to serve as an impartial platform to exchange ideas, broaden perspectives, and support problem-solving during a period of significant geopolitical and societal change.

Fuchs, director of CMU’s Critical Technology Initiative and professor of engineering and public policy, researches how emerging technologies are developed, commercialized, and manufactured, and the policies governments need to support national competitiveness in those areas. Throughout the week in Davos, she will participate in sessions aligning with her expertise on topics such as intelligent infrastructure, workforce development for advanced manufacturing, industrial policy, and the future of research.

Fuchs will also moderate two sessions. The first, titled “How can governments innovate?,” explores how public institutions can adopt more adaptive and experimental approaches to policymaking. By adapting the approach of product designers, the panelists will consider the use of frontier tools, iterative methods, and future-focused perspectives to create bold and adaptive systems that are ready for tomorrow's challenges.

The second session, “AI for Curricular Value Chains,” examines how artificial intelligence can improve material design, efficiency, transparency, and reuse across global production systems, while at the same time enhancing economic competitiveness and supply chain resiliency. Fuchs will oversee discussion on the applications of AI in chemicals, textiles, and electronics, and considerations of the data standards, infrastructure, and cross-industry collaboration necessary to scale circular manufacturing processes.

Her participation builds on two decades of involvement in national and international discussions on technology policy, including at previous WEF meetings and on WEF committees. In 2012, Fuchs was selected as a World Economic Forum Young Scientist and has been an invited speaker at past WEF events, including the Annual Meeting of the New Champions.

Carnegie Mellon University’s Erica Fuchs will join leaders from across government, technology, business, and academia to participate in the World Economic Forum Annual Meeting in Davos, Switzerland from January 19-23, 2026.

Every year, the Forum hosts forward-looking forums and panels to address widespread global challenges from economic stability to digital trust to climate resilience. This year’s theme, A Spirit of Dialogue, aims to serve as an impartial platform to exchange ideas, broaden perspectives, and support problem-solving during a period of significant geopolitical and societal change.

Fuchs, director of CMU’s Critical Technology Initiative and professor of engineering and public policy, researches how emerging technologies are developed, commercialized, and manufactured, and the policies governments need to support national competitiveness in those areas. Throughout the week in Davos, she will participate in sessions aligning with her expertise on topics such as intelligent infrastructure, workforce development for advanced manufacturing, industrial policy, and the future of research.

Fuchs will also moderate two sessions. The first, titled “How can governments innovate?,” explores how public institutions can adopt more adaptive and experimental approaches to policymaking. By adapting the approach of product designers, the panelists will consider the use of frontier tools, iterative methods, and future-focused perspectives to create bold and adaptive systems that are ready for tomorrow's challenges.

The second session, “AI for Curricular Value Chains,” examines how artificial intelligence can improve material design, efficiency, transparency, and reuse across global production systems, while at the same time enhancing economic competitiveness and supply chain resiliency. Fuchs will oversee discussion on the applications of AI in chemicals, textiles, and electronics, and considerations of the data standards, infrastructure, and cross-industry collaboration necessary to scale circular manufacturing processes.

Her participation builds on two decades of involvement in national and international discussions on technology policy, including at previous WEF meetings and on WEF committees. In 2012, Fuchs was selected as a World Economic Forum Young Scientist and has been an invited speaker at past WEF events, including the Annual Meeting of the New Champions.

Carnegie Mellon University’s Erica Fuchs will join leaders from across government, technology, business, and academia to participate in the World Economic Forum Annual Meeting in Davos, Switzerland from January 19-23, 2026.

Every year, the Forum hosts forward-looking forums and panels to address widespread global challenges from economic stability to digital trust to climate resilience. This year’s theme, A Spirit of Dialogue, aims to serve as an impartial platform to exchange ideas, broaden perspectives, and support problem-solving during a period of significant geopolitical and societal change.

Fuchs, director of CMU’s Critical Technology Initiative and professor of engineering and public policy, researches how emerging technologies are developed, commercialized, and manufactured, and the policies governments need to support national competitiveness in those areas. Throughout the week in Davos, she will participate in sessions aligning with her expertise on topics such as intelligent infrastructure, workforce development for advanced manufacturing, industrial policy, and the future of research.

Fuchs will also moderate two sessions. The first, titled “How can governments innovate?,” explores how public institutions can adopt more adaptive and experimental approaches to policymaking. By adapting the approach of product designers, the panelists will consider the use of frontier tools, iterative methods, and future-focused perspectives to create bold and adaptive systems that are ready for tomorrow's challenges.

The second session, “AI for Curricular Value Chains,” examines how artificial intelligence can improve material design, efficiency, transparency, and reuse across global production systems, while at the same time enhancing economic competitiveness and supply chain resiliency. Fuchs will oversee discussion on the applications of AI in chemicals, textiles, and electronics, and considerations of the data standards, infrastructure, and cross-industry collaboration necessary to scale circular manufacturing processes.

Her participation builds on two decades of involvement in national and international discussions on technology policy, including at previous WEF meetings and on WEF committees. In 2012, Fuchs was selected as a World Economic Forum Young Scientist and has been an invited speaker at past WEF events, including the Annual Meeting of the New Champions.

Imagine snapping a photo where every detail, near and far, is perfectly sharp—from the flower petal right in front of you to the distant trees on the horizon. For over a century, camera designers have dreamed of achieving that level of clarity. In a breakthrough that could transform photography, microscopy, and even smartphone cameras, researchers at Carnegie Mellon University have developed a new kind of lens that can bring an entire scene into sharp focus at once—no matter how far away or close different parts of the scene are.

The team, consisting of Yingsi Qin, an electrical and computer engineering Ph.D. student, Aswin Sankaranarayanan, professor of electrical and computer engineering, and Matthew O’Toole, associate professor of computer science and robotics, presented their findings at the 2025 International Conference on Computer Vision and received a Best Paper Honorable Mention recognition.

Imagine snapping a photo where every detail, near and far, is perfectly sharp—from the flower petal right in front of you to the distant trees on the horizon. For over a century, camera designers have dreamed of achieving that level of clarity. In a breakthrough that could transform photography, microscopy, and even smartphone cameras, researchers at Carnegie Mellon University have developed a new kind of lens that can bring an entire scene into sharp focus at once—no matter how far away or close different parts of the scene are.

The team, consisting of Yingsi Qin, an electrical and computer engineering Ph.D. student, Aswin Sankaranarayanan, professor of electrical and computer engineering, and Matthew O’Toole, associate professor of computer science and robotics, presented their findings at the 2025 International Conference on Computer Vision and received a Best Paper Honorable Mention recognition.

Chemical engineering graduates assisted by artificial intelligence (AI) will have the power to speed up scientific discovery, improve the replication of research, and unlock new paths of inquiry. Before they can responsibly combine high-throughput and remote experimentation with machine-learning-driven experimental design, they need skills in three areas.

First, students need domain knowledge. “You have to know about the problem you are solving, or you can’t evaluate the solutions you find,” says John Kitchin. Second, they need a foundation in machine learning to understand the math and ideas behind the models, as well as their capabilities and limitations. Third, students need programming skills. “Even when code is written by a large language model,” says Kitchin, a professor of chemical engineering, “you need the skills to steer the LLM and to evaluate if the code is correct and doing what is needed.”

For students who want the training to integrate AI and chemical engineering more deeply, the Department of Chemical Engineering offers the Master of Science in Artificial Intelligence Engineering-Chemical Engineering (MS in AIE-ChE). These students gain practical experience applying their skills through research. In a current collaborative project, MS in AIE-ChE students are developing a benchmarking testbed for a widely-used chemical process engineering time-series dataset. They are testing machine learning and deep learning models for anomaly detection in industry.

The National Academy of Inventors (NAI) has elected Marios Savvides from Carnegie Mellon University to its 2025 cohort of fellows for his work in applied AI, computer vision, and biometric security.

The NAI Fellows Program was established to highlight academic inventors who have demonstrated a prolific spirit of innovation in creating or facilitating outstanding inventions that have made a tangible impact on quality of life, economic development, and the welfare of society. Election to NAI Fellow status is the highest professional distinction accorded solely to academic inventors.

The National Academy of Inventors (NAI) has elected Marios Savvides from Carnegie Mellon University to its 2025 cohort of fellows for his work in applied AI, computer vision, and biometric security.

The NAI Fellows Program was established to highlight academic inventors who have demonstrated a prolific spirit of innovation in creating or facilitating outstanding inventions that have made a tangible impact on quality of life, economic development, and the welfare of society. Election to NAI Fellow status is the highest professional distinction accorded solely to academic inventors.

River Sepinuck has found a way to combine his long-time interest in 3D printing with his future career ambitions in industrial robotics. The mechanical engineering junior indulges both as a member of Sneha Prabha Narra’s research team.

Narra is an assistant professor of mechanical engineering. A key area of her work is wire arc additive manufacturing (WAAM), which is a 3D printing process that uses a robotic arm to move a welding torch that melts metal wire feedstock with an electric arc heating source. WAAM is capable of producing metal parts that are significantly larger than those produced using powder-based additive manufacturing methods.

Sepinuck used the Highway to Undergraduate Research in the Academic Year (HURAY) program to find his way onto Narra’s team, where he worked under the direction of Gala Solis, a doctoral student in mechanical engineering. Solis studies WAAM process monitoring using thermal imaging with commercial-grade cameras and a ratiometric method to measure accurate real-time temperatures while eliminating the dependence on emissivity. Monitoring these temperatures is critical for process control, ensuring the quality, consistency, and integrity of the metal parts being built.

River Sepinuck has found a way to combine his long-time interest in 3D printing with his future career ambitions in industrial robotics. The mechanical engineering junior indulges both as a member of Sneha Prabha Narra’s research team.

Narra is an assistant professor of mechanical engineering. A key area of her work is wire arc additive manufacturing (WAAM), which is a 3D printing process that uses a robotic arm to move a welding torch that melts metal wire feedstock with an electric arc heating source. WAAM is capable of producing metal parts that are significantly larger than those produced using powder-based additive manufacturing methods.

Sepinuck used the Highway to Undergraduate Research in the Academic Year (HURAY) program to find his way onto Narra’s team, where he worked under the direction of Gala Solis, a doctoral student in mechanical engineering. Solis studies WAAM process monitoring using thermal imaging with commercial-grade cameras and a ratiometric method to measure accurate real-time temperatures while eliminating the dependence on emissivity. Monitoring these temperatures is critical for process control, ensuring the quality, consistency, and integrity of the metal parts being built.

In the 1800s, people weren’t asking for cars, they just wanted to get from point A to point B faster. In the early 2000s no one was seeking out social media, they just craved more connection at home. That’s the challenge in product development: people have countless desires, but they can’t easily articulate a solution that doesn’t exist yet. Product designers know that understanding those preferences is essential to developing a meaningful solution, but weeding out what’s relevant in a sea of opinions is hard.

A new Large Language Model powered tool from Jon Cagan and Vince Sha converts wants and needs into succinct product attributes and requirements to help product designers think more strategically about solutions.

The tool, VOA LLM Bot, is based on the widely successful Value Opportunity Analysis (VOA) that, since its creation by Cagan and Craig Vogel, has helped to produce award-winning products, re-organize corporate structures, and teach students how to innovate.

VOA identifies seven opportunities to add value to a product:

• Emotion, Does the product appropriate and engage feelings?
• Aesthetics, Does the product entice all of the senses it’s supposed to?
• Identity, Does the product have a unique personality, different from its competitors?
• Ergonomics, Is the product easy and safe to use?
• Impact, Will the product align with customers’ social values?
• Core technology, Is the product enabling and reliable?
• Quality, Is the product durable?

“Products enable an experience for the user, so the better the experience, the greater the value of the product to the consumer,” said Cagan, department head and professor of mechanical engineering. “VOA helps designers understand what is most important to users and other stakeholders during the product experience.”

“The VOA LLM Bot is like a directed ChatGPT for product designers,” said Sha, associate dean of IT and operations at CMU’s Dietrich College of Humanities and Social Sciences and technical lead for the Open Forum for AI. The VOA LLM Bot is built on the Dietrich Analysis Research Education (DARE) open-source platform, designed to provide a suite of tools for human-centric applied AI innovation.

It helps users to create a VOA, capturing and reporting their ideas and thoughts, then compares their goals to current products through a product opportunity gap analysis, and to uncover where a to-be-created product needs to focus and differentiate in order to be successful in the marketplace.

“The bot is flexible and responsive, allowing users to dive deeper into topics of interest or change design direction. This flexibility ensures users retain their agency and autonomy over the design process, which we believe is critical to encouraging creativity,” Sha said. “Once the bot has gathered all of the necessary information from the designer, it generates a product requirements document to show the designer what features the future product should have to provide consumers grounded in needs, wants, and even desires from the VOA report.”

For example, a conversation between a designer looking to build a service to help mobility impaired people get around and the VOA LLM Bot might look like this:

AI: Since you’re designing a service, let’s start exploring these VOA categories to better understand what matters most in your project. Let’s take them one by one. For Emotion, what attributes (adventure, independence, security, sensuality, confidence, power) do you think are most relevant to your mobility service?

User: I think all except sensuality 

AI: Thanks! Can you tell me a bit more about why these specific attributes are important to help mobility impaired people get around? What do these emotions mean for your target users?

Once the bot has collected all of the information, it provides the user with product attributes like these requirements for a driving service and a vehicle driver to ensure security needs are met:

Driver Requirements: Must implement rigorous driver screening including background checks, driving record, drug and alcohol screening. Must provide specialized training for drivers including safe operation accessibility equipment, effective communication with disabled users, and emergency situation management. 

Of course a more extensive and complete set of requirements are generated to provide the complete understanding of what the product must do and deliver.

When Vijayakumar Bhagavatula gave the opening remarks at the recent Milestone Moments talk, the interim dean of the College of Engineering seemed to genuinely wonder what the secret was to Maysam Chamanzar’s success.

In addition to touting the vitally important neuroscience breakthroughs the professor of electrical and computer engineering (ECE) has made in the development of next-generation brain-computer interfaces, Bhagavatula also marveled at the unusually high faculty course evaluations scores he received teaching Electromagnetics, one of the program’s toughest courses.

Chamanzar’s scores were not just high, they were a perfect 5.0 out of 5.0, noted Larry Pileggi, department head and professor of electrical and computer engineering, when he introduced Chamanzar.

“He is an incredible lecturer, and his research work is inspiring,” said Pileggi.

Chamanzar then revealed what may well be the secret to his success: the accomplished engineer is a philosopher at heart.

Chamanzar shared how his philosophy of life has guided his path and driven many of his achievements during his talk at the Center for Faculty Success’ fifth Milestone Moments event, which celebrates professors who have achieved the highest rank within their respective faculty tracks.

He says his upbringing in a close-knit Iranian family who valued education and learning led him to study philosophers like Nasir al-Din Tusi, the famous Persian polymath, astronomer, architect, physician, and scientist, who, like Chamanzar, wanted to understand the world through both science and philosophy.

Chamanzar who described the unexpected turns his career has taken declared, “When the destination is uncertain, the journey becomes wonderful and exciting."

Carnegie Mellon University Africa has partnered with the National Basketball Association Africa (NBA Africa) on a startup accelerator program that aims to support the next wave of early-stage African startup businesses transforming the sports and creative sectors. The NBA Africa Triple-Double Accelerator was launched by the league last year to support the continent’s technology ecosystem and the next generation of African entrepreneurs.

NBA Africa announced the partnership in a recent press release, as well as the 10 African startup companies that have been selected as finalists. The finalists will pitch their products to a panel of international industry leaders at an event, called Demo Day, which will be held at CMU-Africa in Kigali, Rwanda on December 5.

Five winners will be chosen to receive financial support and the opportunity to join CMU-Africa’s 12-month Business Incubation Program in their Innovation Hub, which helps African tech startups transform proof-of-concept prototypes and preliminary market assessments into scalable, market-ready products and services.

The 10 finalists who will pitch on Demo Day include:

• Athlon Technology (Egypt) aims to leverage accessible mobile technology and AI to provide video analysis for amateur and budget-constrained sports teams while addressing a market gap with a user-friendly, hardware-light solution.
• Atsur (Nigeria) leverages blockchain technology to promote investment in African art and support artists and art communities.
• CoLab (South Africa) is a platform that brings together creatives, entrepreneurs and industry professionals, providing a space to connect, manage projects and bring ideas to life.
• Contestify (Nigeria) is an all-in-one platform that streamlines contest management, offering real-time judging, transparent scoring and instant payouts.
• Fitclan (Egypt) is a digital fitness hub that leverages a flexible subscription model for individuals and corporate clients.
• Novate (Morocco) offers a unique, immersive virtual reality (VR) football viewing experience with features such as seat selection, camera switching, social voice chat, and live stats.
• ProPath Sports (Kenya) revolutionizes athlete discovery in Kenya with data-driven talent identification; its iSTEAM program covers all aspects of talent development.
• Reborn (Morocco) offers comprehensive performance indicators that give athletes deep insights into their physical condition and on-field performance, essential for identifying strengths, areas for improvement, and optimizing overall performance.
• Safia Health (Kenya) offers personalized training regiments that integrate fitness, recovery and mental wellbeing tracking into a unified platform, offering value to athletes and coaches.
• SongDis (Nigeria) provides comprehensive digital distribution and services tailored for African independent artists and labels. 

If you’ve ever moved into a new home, you know the challenge of packing a moving truck—it’s like solving a giant, three-dimensional puzzle. Everything needs to fit just right, and nothing can be left loose or unbalanced, or it risks shifting and breaking in transit. For humans, balancing objects, whether it’s a tray of food or a stack of moving boxes, comes naturally thanks to the coordination between our muscular and vestibular systems. But for robots, maintaining balance while carrying loads is far more complex. They must constantly track both the position of the object and their own body to make real-time adjustments to stay upright.

To overcome this challenge in robotics, researchers in the Department of Mechanical Engineering at Carnegie Mellon University have developed a tactile sensor that enables a four-legged robot to carry unsecured cylindrical objects on its back for long distances.

An estimated one trillion species of microorganisms reside on Earth, yet scientists have been able to study less than two percent of them. Because many microorganisms cannot be cultivated in laboratories, researchers at Carnegie Mellon University are creating technology to cultivate them in the field.

Better tools for culturing previously unknown microbial species may lead to novel antibiotics or other therapeutic products. Tagbo Niepa developed a microcapsule system to cultivate microorganisms in their natural environment, rather than in laboratory conditions, where they behave differently.

Because each microcapsule can hold a nanoliter volume of microbial culture, these tiny bioreactors are referred to as “nanocultures.” Microorganisms natively found in soil, for example, can be sequestered inside nanocultures, which can then be put back into the soil.

An estimated one trillion species of microorganisms reside on Earth, yet scientists have been able to study less than two percent of them. Because many microorganisms cannot be cultivated in laboratories, researchers at Carnegie Mellon University are creating technology to cultivate them in the field.

Better tools for culturing previously unknown microbial species may lead to novel antibiotics or other therapeutic products. Tagbo Niepa developed a microcapsule system to cultivate microorganisms in their natural environment, rather than in laboratory conditions, where they behave differently.

Because each microcapsule can hold a nanoliter volume of microbial culture, these tiny bioreactors are referred to as “nanocultures.” Microorganisms natively found in soil, for example, can be sequestered inside nanocultures, which can then be put back into the soil.

In the 1980s when micro-electro-mechanical systems (MEMS) were first created, computer engineers were excited by the idea that these new devices that combine electrical and mechanical components at the microscale could be used to build miniature robots.

The idea of shrinking robotic mechanisms to such tiny sizes was particularly exciting given the potential to achieve exceptional performance in metrics such as speed and precision by leveraging a robot’s smaller size and mass. But making robots at smaller scales is easier said than done due to limitations in microscale 3D manufacturing.

Nearly 50 years later, Ph.D. students Steven Man and Sukjun Kim, working with Mechanical Engineering Professor Sarah Bergbreiter, developed a 3D printing process to build tiny Delta robots called microDeltas. Delta robots at larger scales (typically two to four feet in height) are used for picking, placing, and sorting tasks in manufacturing, packaging, and electronics assembly. The much smaller microDeltas have the potential for real-world applications in micromanipulation, micro assembly, minimally invasive surgeries, and wearable haptic devices.

Previous methods for making robotic mechanisms at these smaller sizes required manual assembly and folding of microfabricated components.

Bergbreiter’s team developed a 3D printing process for microrobotics that uses two-photon polymerization, an advanced nanofabrication technique in which a focused laser solidifies photosensitive material with extremely high precision. Then a thin metal layer is deposited that enables electrical functionality for the complex 3D geometries and actuators without folding or manual assembly.

“Eliminating the need for assembly has huge benefits in terms of rapid fabrication and design iteration,” said Bergbreiter. “At large scales, researchers can assemble robots from motors and mechanisms that you can buy off-the-shelf. We don’t have that luxury at these small scales where both making and connecting tiny pieces together is hard. That’s where this new fabrication process is incredibly beneficial.

Concrete 3D printing reduces both time and cost by eliminating traditional formwork, the temporary mold for casting. Yet most of today’s systems rely on extrusion-based methods, which deposit material very close to a nozzle layer by layer. This makes it impossible to print around reinforcement bars (rebars) without risk of collision, limiting both design flexibility and structural integrity of builds.

Kenji Shimada and researchers in his Carnegie Mellon University’s Computational Engineering and Robotics Laboratory (CERLAB), are breaking through that limitation with a new simulation tool for spray-based concrete 3D printing.

Although there’s no medal at the end of the Phonon Olympics, for Alan McGaughey, the collaboration required to evaluate the accuracy of three widely used open-source thermal conductivity calculation packages was worth more than gold.

For the last decade, researchers seeking to understand the properties of new materials have turned to open-source packages to perform thermal conductivity calculations. These packages enable a broader community to study thermal transport, but until now users had no way of knowing whether or not each package would produce consistent and accurate results.

Coordinated by McGaughey, six teams participated in the “Phonon Olympics” to test each of the three most cited packages: ALAMODE, phono3py, and ShengBTE. For each package, one team was made up of the developers while the other consisted of expert users. Each team conducted benchmark calculations for four materials: geranium, rubidium bromide, monolayer molybdenum diselenide, and aluminum nitride. As published in the Journal of Applied Physics, the thermal conductivities calculated by the teams fell within 15% of their mean values for each of the four materials.

Among the job seekers at a recent job fair hosted by Carnegie Mellon University’s Manufacturing Futures Institute (MFI), was a group of participants from the Step on Up – Maker to Manufacturer program.

Every other week for six months, 25 participants were introduced to various manufacturing skills and equipment at sessions hosted by MFI, Prototype PGH, and New Century Careers. The unique experience seeing and using these tools and machinery sparked a genuine interest in the manufacturing career opportunities the program was designed to encourage them toward.

One exhibitor at the job fair was so impressed with their knowledge and enthusiasm that he hopes to find ways for his company to support the program and look to it as a source for future talent.

Teamwork may fuel effective ideas, even at times better than a single person has the ability to generate on their own, but even the best groups need guidance. Teams become most effective when there is a facilitator who keeps conversations on track, draws out quieter voices, and helps steer decisions. To guide collaboration, researchers at Carnegie Mellon University introduce AI Coach, a novel artificial intelligence agent that can perform as well as, if not marginally better, than a human manager.

Backed by psychology-informed artificial intelligence, AI Coach doesn’t need to be trained on prior problem-solving examples to be successful. Instead, it monitors teams’ collective intelligence.

“Training AI for every problem-solving scenario is impractical,” said Chris McComb, associate professor of mechanical engineering. “If an AI can understand how members of a team contribute to the conversation, assess how aligned they are on the same goals, and prevent individuals from becoming disengaged, then the team will design better solutions regardless of what problem they’re solving.”

Burcu Akinci, head of the Department of Civil and Environmental Engineering (CEE), has been appointed the next Dr. William D. and Nancy W. Strecker Dean of the College of Engineering at Carnegie Mellon University, effective January 1, 2026.

A member of the CMU community for nearly 25 years, Akinci is an exceptional leader who brings the strategic vision, research impact, and collaborative spirit necessary to lead the College of Engineering. Akinci served as associate dean for research for six years, driving institutional-level growth by helping to establish the “moonshot initiative” to cultivate large-scale research centers, developing the college’s strategic research direction, and increasing the value of new research awards.

As department head, Akinci fostered a culture of collaboration among students, faculty, staff, alumni, and external partners, encouraging shared learning and the open exchange of ideas across all levels of the department. Through initiatives such as the alumni-to-student and Ph.D.-to-Ph.D. mentorship programs, as well as the Industry Partnership Program that connects students directly to opportunities at more than 20 leading engineering firms, she helped drive innovation by creating pipelines for meaningful engagement.

Under her leadership, the department also expanded its graduate offerings, including CEE’s first online certificate program, AI Engineering - Digital Twins & Analytics, and a new interdisciplinary master’s degree in the emerging field of civil and computer engineering.

When robots are built with biological materials, they have the potential to achieve remarkable behaviors typically only seen in nature. For example, unlike traditional actuators, actuators built from muscle tissue can adapt and grow stronger with use. This means that a robot powered by living muscle doesn’t just move—it exercises and gains the ability to adjust to its environment and perform tasks more efficiently over time.

In order to deploy biohybrid robots for specific tasks, researchers must first understand how to design and control robots who can get stronger over time. The Biohybrid and Organic Robotics Group, led by Vickie Webster-Wood, has created a model to support just that. By using reinforcement learning, their approach learns to control a model of a biohybrid robot, even as the muscles get stronger each time they attempt the task.

Stepping into the offices of Near Earth Autonomy is a bit like stepping into a robotics exhibit at a science center. Various modules, sensors, and technologies line the wall, proudly displayed in the order they were developed, like a hall of fame for autonomous flight.

Two electrical and computer engineering doctoral students were among the 10 from Carnegie Mellon pursuing artificial intelligence research who will receive support from Amazon through the company’s new AI Ph.D. Fellowship Program. The remaining students come from the school of Computer Science and College of Engineering.

The students’ research tackles the foundational challenges, theoretical underpinnings, and deep technological systems critical to AI innovation.

“Close collaboration between academia and industry is critical to producing groundbreaking work that will shape technologies for years to come,” said Martial Hebert, dean of the School of Computer Science. “Amazon and Carnegie Mellon share a common vision that AI can transform how we work, play, shop, socialize, and learn. We are grateful for Amazon’s support of foundational research in pursuit of innovation.”

Amazon’s AI Ph.D. Fellowship Program aims to help drive the innovations that will underwrite the next step in the evolution of practical AI. The program will provide two years of funding for more than 100 Ph.D. students at nine universities who are pursuing research on core AI disciplines such as machine learning, computer vision, and natural language processing.

"Amazon’s AI Ph.D. Fellowship Program reflects our ongoing commitment to the academic community. We're fortunate to collaborate with some of the nation's brightest Ph.D. students who are advancing critical areas in AI—from high-performance chips and hardware to networking, software, foundation models, applications, and more,” said Rohit Prasad, a senior vice president and head scientist for Amazon AGI. “What makes this program special is how it brings together Amazon's real-world experience across diverse industries with the fresh perspectives of these top researchers to cultivate the next generation of AI leaders. We believe investing in future talent is essential to moving the field forward and creating truly useful AI that benefits everyone.”

Amazon selected students for the program from CMU; Johns Hopkins University; the Massachusetts Institute of Technology; Stanford University; the University of California, Berkeley; the University of California, Los Angeles; the University of Texas at Austin; the University of Illinois Urbana-Champaign; and the University of Washington.

The $68 million program provides $10 million in student funding each year and $24 million annually in Amazon Web Services (AWS) cloud-computing credits. Each fellow is also paired with an Amazon mentor, a senior scientist working at Amazon on a topic related to the fellow’s work. Mentors will meet regularly with their fellows to offer guidance and to discuss the real-world implications of the fellows’ research.

Amazon’s AI Ph.D. Fellowship Program builds on the company’s long history of supporting academic research. Amazon and CMU recently announced the launch of the CMU-Amazon AI Innovation Hub to bolster research on generative AI, robotics, natural language processing and cloud computing technologies. Faculty and student research have received funding through the Amazon Scholar program and Amazon Research Awards, and AWS committed to supporting CMU CS Academy, allowing the free computer science curriculum for middle and high school classrooms to be hosted on its servers at no cost.

In addition to supporting foundational research, Amazon, with support from Gov. Josh Shapiro and other government leaders, announced this summer plans to invest at least $20 billion in Pennsylvania to expand its data center infrastructure for AI and cloud computing.

For more information on the AI Ph.D. Fellowship Program, visit the Amazon Science website.

The following students are part of the inaugural fellowship cohort.

Apurva Gandhi - Computer Science Department (CSD)

Aviation accounts for 10 percent of U.S. transportation greenhouse gas (GHG) emissions and roughly three percent of the nation’s total GHG production, including carbon dioxide (CO₂). But the effects of airplane travel on the environment extend to more than just CO₂. These non-CO₂ effects known as contrails—the long, white streaks behind airplanes in the sky—have historically received far less attention than decarbonization efforts. But Han Ding is hoping to change that.

Ding, a mechanical engineering graduate student in Hamish Gordon’s group, has worked as an intern at Boeing for the past two summers. As a member of Boeing’s Graduate Researcher Program (GRP), Ding contributed to advanced modeling and sustainable aviation research, including the development of high-resolution weather simulation workflows for contrail forecasting and mitigation. Her work supported Boeing’s efforts to reduce aviation’s environmental impacts while building cross-functional bridges between research, data engineering, and real-world applications in the global aviation industry.

The radio spectrum is a fundamental resource for wireless communication. Cellular networks, WiFi, and bluetooth are all examples of wireless systems that depend on the radio spectrum. Researchers from Carnegie Mellon University have developed a soft antenna to better utilize radio waves, increasing connectivity and communication.

Historically, antennas are rigid metallic devices that need to be pointed in a specific direction to connect to the radio spectrum. Most programmable radios today either require mechanical or electronic switching between antennas, or wide-band antennas. With radio frequency being tunable, a static antenna can easily lose connection to the frequency. By introducing a soft, flexible antenna, the device can sense and move to the most efficient radio frequency available.

Researchers in Carnegie Mellon’s College of Engineering have developed Softenna, a first-of-its-kind soft-robotic highly reconfigurable antenna platform that dynamically adapts its radio frequency properties, including center frequency, beam pattern, directionality, and polarization. Softenna achieves this through a combination of mechanical and electronic reconfiguration.

“This is an unusual interdisciplinary project where we want to leverage advances in shape-shifting materials and surfaces from robotics for wireless antenna and meta-surface design,” says Swarun Kumar, professor of electrical and computer engineering, director of the WiTech Lab, and lead on the project.

For the estimated 1.2 million Americans living with limb loss, transplants offer a renewed opportunity for function, independence, and quality of life. Why then are fewer than four VCA transplants performed across the U.S. annually?

Vascularized Composite Allograft (VCA) transplantation is a complex procedure that requires highly specialized surgical teams to preserve and reconnect multiple types of tissue including skin, muscle, bone, blood vessels, and nerves. Similar to other types of transplants, recipients must take lifelong immunosuppressant medication to prevent their body from rejecting the transplant. However, the complexity of this multi–tissue procedure makes it more difficult for surgeons to preserve and accurately assess the viability of the tissue to predict acceptance.

With the goal of making transplants more accessible and better matched, Jessica Zhang, professor of mechanical engineering at is leveraging AI to assist autonomous monitoring and keep donor limbs alive outside of the body.

In collaboration with the originating PI John Brassil at Functional Circulation LLC, Dr. Byoung Chol Oh at Johns Hopkins School of Medicine and Dr. Xiangliang Zhang at University of Notre Dame, Zhang’s team will use normothermic machine perfusion (NMP), a process that pumps donor limbs with warm, blood-like fluid to keep them alive by simulating conditions inside the body. Unlike cold storage, which can only preserve an organ for four to six hours, NMP has the potential to extend that timeline. However, NMP alone cannot capture the complexity of real, physiologic life.

Disaster just struck, roads are inaccessible, and people need shelter now. Rather than wait days for a rescue team, a fleet of AI-guided drones takes flight carrying materials and the ability to build shelter, reinforce infrastructure, and construct bridges to reconnect people with safety.

It sounds like science fiction, but new research from Carnegie Mellon University’s College of Engineering combines drones, additive manufacturing, and large language models to rethink the future of aerial construction.