2026 ANNUAL MODELING AND SIMULATION CONFERENCE (ANNSIM)

Track chair:

• Deniz Cetinkaya, dcetinkaya@bournemouth.ac.uk

Track co-chairs:

• Lam Shao Wei Sean, gmslasws@nus.edu.sg
• Ashish Kumar, ashish.kumar@duke-nus.edu.sg 

Modeling and Simulation (M&S) is currently at the core of many industrial processes. It is a vital component, supporting early evaluation and optimization of designs, as well as ongoing verification to ensure that the right product is developed with the required quality. However, there are still businesses that need to understand the benefits of embracing M&S in project development and management, which can be demonstrated through real-world examples of success.

Real-world applications have always been the driving force behind the development of M&S theories. For over 50 years, the Annual Simulation Symposium (ANSS) has been a forum for exchanging ideas, results, and methods related to real-world theories and applications of M&S for simulationists in industry, government, and academia.

The purpose of this track is to highlight and advance rigorous experimental and computational practices of M&S devoted to the study of real-world problems. Research on all topics concerning the practice of M&S theories is welcome. Authors are invited to present research of all kinds, including case studies and applications.

Recommended topics in the track include, but are not limited to, the following with application to real-world problems:

• Advances in the field of M&S for design, implementation, and evaluation purposes.
• Application of modeling formalisms into real-world applications.
• Rigorous comparisons across M&S techniques.
• New applications of M&S.
• Novel uses of M&S in real-world applications.
• Application of M&S to co-design, hardware-in-the-loop, co-simulation.
• M&S methods and tools: performance analysis, scalability, reproducibility, reusability, open simulation, etc.

Track chairs

• Abdolreza Abhari, Toronto Metropolitan University, Toronto, Canada, aabhari@torontomu.ca
• Cheng-Bang Chen, cxc1920@miami.edu

The CNS track emphasizes the vital role of communications and networking in modern systems. While it initially centered on traditional computer networks, its scope now includes the Intelligent Internet of Things (IIoT), 5G/6G technologies, and smart telecommunication systems. The track also explores the transformative impact of Edge and Cloud computing, understanding their potential in shaping AI network-based systems for building the foundation and infrastructure of smart cities.

The CNS forum serves as a premier platform for professionals to exchange insights on the performance evaluation of both current and emerging new generations of communication, energy, and healthcare network systems. Embracing a diverse spectrum, we are keen on contributions that range from theoretical research to hands-on practical investigations. Work that presents innovative evaluation methods or offers insights into design and performance optimization in communications and network systems is especially valued. Whether it is experimental analysis, system optimization, artificial neural networks, using AI and Machine Learning in networking, or real-world case studies, all pertinent contributions that align with these themes (but not limited to the following topics) are warmly welcomed.

Topics of Interest:

• AI and ML in communications, networking, and computer systems.
• Data Science, Big Data Analysis in communications, networking, and computer systems.
• 5G/6G and Beyond and enabling technologies, Device to Device communications, and network routing.
• Software Defined Networking and Network Function Virtualization.
• Edge/Fog/Cloud Computing, Distributed Systems, and Scalable Machine Learning Networks.
• Green and energy-efficient communications and networking.
• Cooperative communications and networking.
• Cognitive radio and networking, Future Radio Access Networks.
• Web social network modeling and simulation, socially aware networking and applications.
• Vehicular ad-hoc networks / connected vehicles.
• Traffic modeling and simulation of telecommunication systems and networks, large-scale networks simulation.
• Trust and security in communications, networking, and computer systems and enabling technologies.
• Web-based systems and simulation of video analytics applications.
• Optical-Wireless communication and systems, Wireless ad-hoc Networks/ Wireless Sensor Networks/ Delay Tolerant Networks/ Opportunistic Networks/ Peer-to-Peer networking and computations.
• Next Generation Internet of Things, enabling technologies and intelligent applications (Architecture, networking technologies, smart cities, healthcare systems, smart environment, smart mobility, precision agriculture, smart sustainability).

Track chairs:

• Mamadou Kaba Traore, mamadou-kaba.traore@u-bordeaux.fr
• Joost Mertens, University of Antwerp, Antwerp, Belgium, Joost.Mertens@uantwerpen.be

Cyber-Physical Systems (CPS) and Digital Twins (DT) are pivotal in modern technological advancements, with applications ranging from autonomous vehicles and smart manufacturing to precision healthcare and smart energy systems. The integration of CPS and DT brings forth numerous challenges due to the complex behavior of heterogeneous components interacting with each other and their environments. Digital twinning, in particular, is a transformational trend that enables real-time synchronization of a digital model with its physical counterpart, providing descriptive, diagnostic, predictive, and prescriptive functionalities. These functionalities are often enabled by simulation, making the development of accurate and efficient simulators crucial.

This track invites submissions that address the development, integration, and application of CPS and Digital Twins, with a focus on new approaches in Modeling and Simulation (M&S) to support the development and operation of these systems throughout their lifecycle, including design, verification, and operational phases. Researchers and practitioners are invited to share their innovations, addressing key challenges and demonstrating solutions across diverse application domains. It aims to provide a forum for researchers and practitioners to exchange their latest results and experiences 

Submissions may address topics either in the broader context of cyber-physical systems or focus specifically on digital twins, including but not limited to:

• Applied modelling and (co-)simulation
• Simulation-based digital twins
• Model creation and recommendation systems
• Collaborative modelling and simulation
• Machine learning, data analytics and data-driven development techniques
• Low-code development techniques
• Architectural patterns of simulators in digital twinning
• Fidelity, scalability, reliability, trust, and security of simulators
• Standards, standardization, and certification of simulators 
• Verification, Validation, and Uncertainty Quantification (VVUQ)
• Techniques for handling uncertainty, reliability, and explainability
• (Co-)simulation-based verification, optimization, and monitoring
• Digital twins for dynamic system (re)configuration and optimization
• Digital twins in support of the Digital Thread
• Human factors in digital twins, such as simulation for or by the human-in-the-loop, digital twins as a training environment, etc.
• Case studies, industry applications, and experience reports

Track chairs

• Xiaoli Hu, xhu@gsu.edu
• Charles (Chick) Macal, macal@anl.gov 

The term “human agent” combines concepts such as artificial societies, virtual crowds and synthetic populations. These concepts are used in various fields, such as smart city planning, emergency management and national security. Agent-based simulation models involving human agents can capture the decision-making processes of individuals as they interact with and respond to other individuals and their environment. They are also used for various research tasks, such as policy decision support, what-if scenarios, predictive modeling, and guiding data collection.

Of particular interest are artificial societies in which the behavior of individual agents is guided by findings from computational social sciences and calibrated using data from the real world. These heterogeneous, often cooperative agents participate in social networks, which can be physical (e.g. workplaces, schools, sporting events) or virtual (e.g. chat groups with shared interests). Human agents are generally mobile in an environment where they are exposed to social factors and physical constraints. Since multi-agent systems are based on the distributed AI paradigm, autonomy and learning, e.g. in the form of reinforcement learning, are essential components of the system.

Despite the many applications and resulting publications, fundamental methodological challenges remain in modeling realistic human behavior. These challenges include the representation of agents, cooperative behavior, individual and collective learning, the construction of behavioral rules, the incorporation of behavioral theories and their assumptions, the validation and calibration of models representing complex social phenomena, and the detection and management of emergent behavior at the societal level.

Therefore, authors are encouraged to submit papers related to, but not limited to, the following areas:

• Design and implementation of human agents and artificial societies (e.g., case studies, analyses of moral and ethical considerations).
• LLM (Large Language Model)-based agents.
• Learning / intelligent agents.
• The role of the non-stationary environment for the simulation result.
• Applications of human agents and cooperative artificial societies (e.g. modeling of group decisions and collective behavior, emergence of social structures and norms, dynamics of social networks).
• Data collection for artificial societies (e.g., using simulations to identify data gaps, population simulations with multiple data sources, use of the Internet of Things).
• Participatory modeling and simulation.
• Policy development and evaluation through simulations.
• Improved models of social behavior.
• Simulations of societies as public educational tools.
• Mixed-methods (e.g., analyzing or generating text data with artificial societies, combining machine learning and artificial societies).
• Models of individual decision-making, mobility patterns, or socio-environmental interactions.
• Testbeds and environments to facilitate artificial society development.
• Addressing long-standing challenges (model validation, re-use, communication).

Track chairs

• Jalal Possik, jalal.possik@univ-catholille.fr
• Dirk Reiners, dirk.reiners@ucf.edu

This track explores the latest developments and applications of virtual, mixed, and extended reality technologies in modeling and simulation. We welcome papers that showcase innovative uses of immersive environments for training, visualization, human performance enhancement, digital twins, and interactive system design. Submissions may include novel methodologies, tools, frameworks, and case studies that demonstrate how VR/MR/XR advances understanding, decision-making, and user engagement across domains such as defense, healthcare, education, and industry.

We welcome in this track a broad range of topics including mut not limited to:

• ⁠Immersive Technologies in Design Visualization and Collaboration
• AI and Machine Learning for VR/MR/XR
• Testing, evaluation, and validation of Immersive technologies
• Immersive VR/MR/XR platforms for training and education
• Virtual humans and intelligent agents in simulated environments
• Integration of XR with digital twins and real-time simulation
• Human factors, ergonomics, and user performance in immersive systems
• XR-enabled collaboration for distributed simulation
• New hardware and interface technologies (haptics, eye tracking, spatial audio)
• XR-based decision support and mission rehearsal tools
• Cognitive and behavioral modeling in immersive environments
• Assessment and validation methods for XR-based simulation
• Case studies in defense, healthcare, transportation, and smart cities

Track chairs

• Sean Mondesire, Sean.Mondesire@ucf.edu 
• Bulent Soykan, Bulent.Soykan@ucf.edu 

Modeling and Simulation (M&S) have made significant strides in enhancing our understanding of complex systems, improving the ability to predict future states, and enabling the development of (near-)optimal interventions and policies across diverse domains. With the rapid advancements in artificial intelligence and machine learning (AI/ML), there is now unprecedented potential to optimize simulation parameters, train agent behaviors dynamically, and adapt simulation environments through real-time observations and evolving data. The goal of this track is to expand the horizons of human knowledge by integrating the latest AI/ML technologies with M&S.

This Machine Learning and AI in Simulation (MLAIS) track provides a dedicated platform to share insights, research methodologies, and applications that address the intersection of AI/ML and M&S. It focuses on exploring how cutting-edge AI/ML techniques such as knowledge reasoning, computer vision, natural language processing, deep learning, and reinforcement learning can enhance Modeling and Simulation practices and, conversely, how Modeling and Simulation can be leveraged to advance AI/ML solutions. We invite full papers (up to 12 pages) presenting original research on the use of AI/ML in Modeling and Simulation, as well as interdisciplinary work that pushes the boundaries of both fields. Oral presentations will be the format for this track, fostering dynamic discussions around innovative ideas and findings. Topics of interest include, but are not limited to:

• Enhancing validation and verification (V&V) processes with AI and ML
• AI/ML techniques for training and evolving autonomous agents within simulations
• Best practices for the convergence of AI, ML, and simulation
• Using M&S to generate synthetic data for training AI/ML models
• Empirical evaluations of state-of-the-art AI/ML methods in M&S
• Facilitating experimentation and simulation optimization using AI/ML
• Using M&S as a tool to advance AI/ML research and solutions
• Developing simulation modeling tools and methodologies that integrate AI/ML
• Visionary approaches for the future of AI/ML in simulation

This track aims to explore and uncover the full potential of AI/ML in driving the next generation of M&S innovations.

Track chairs

• David Mohaisen, David.Mohaisen@ucf.edu 
• Danda Rawat, Howard University, Washington, DC, USA, db.rawat@ieee.org

Modeling and Simulation as well as digital twin has the ability to improve our understanding and gain better insights into the exploitability and impact of the threat landscape in cyber systems underpinning several critical infrastructures. The emergence of the Internet of Everything has resulted in the growth in interactions between humans, physical and cyber systems and there is an increased need to understand how these interactions could be exploited by adversaries. Modeling and simulation provide a cost-effective means to support research, development, refinement, deployment, and evaluation of the next generation of security solutions for preventing, detecting, and recovering from cyber-attacks and failures. The goal of this track is to provide a forum to present and discuss advancements in research, tools, techniques, solutions, best practices, and heuristics related to the modeling and simulation of cybersecurity. The symposium will address all aspects of modeling, analyzing, design, simulation, implementation, deployment and management of security algorithms, protocols, architectures and systems. We encourage submissions related to all aspects of cybersecurity in a modeling and simulation context in a broad spectrum of application areas.

Topics of interest include, but are not limited to:

• Digital twins for cybersecurity for emerging systems
• Formal models for cybersecurity simulation
• Cybersecurity evaluation and assessment approaches
• Test beds and experimental infrastructure for cybersecurity simulation
• Simulation platforms for cybersecurity assessment
• Hybrid simulations for cyber physical system security
• Modeling and Analysis of Networked security systems
• Modeling security and privacy in mobile and cellular networks
• Modeling security for future Internet architectures
• Risk assessment and management
• Systems engineering for security

Track chairs

• Bulent Soykan, Bulent.Soykan@ucf.edu
• Adan Vela, Adan.Vela@ucf.edu

Global trade, e-commerce growth, and evolving consumer demands are driving rapid changes in logistics, supply chains, and transportation systems. These domains must operate under increasing complexity, uncertainty, and disruption, whether caused by market shifts, geopolitical events, pandemics, or extreme weather. The integration of new technologies—such as automation, artificial intelligence, autonomous vehicles, and advanced analytics—offers opportunities to enhance efficiency, resilience, and sustainability, but also introduces new design, coordination, and risk management challenges.

Modeling and Simulation (M&S) provides essential tools for analyzing, optimizing, and predicting the performance of interconnected logistics, supply chain, and transportation networks. Simulation enables experimentation with new operational strategies, assessment of resilience under disruptions, evaluation of technology adoption scenarios, and data-driven decision-making without costly real-world trials.

This track invites papers that present novel M&S methodologies, tools, and applications that address current and emerging challenges in the movement of goods, services, and people. We welcome both theoretical and applied contributions, as well as interdisciplinary work combining engineering, computer science, operations research, economics, and policy.

Topics of interest include, but are not limited to:

• Supply chain design, optimization, and resilience modeling.
• Simulation-based approaches to logistics network planning.
• Modeling freight, passenger, and multimodal transportation systems.
• Digital twins for logistics and transportation infrastructure.
• Simulation for last-mile delivery and e-commerce fulfillment.
• Agent-based and system dynamics models for supply chain behavior.
• Risk, uncertainty, and disruption modeling in global supply networks.
• Integration of autonomous vehicles, drones, and robotics in logistics.

Track chairs

• Michel Audette, Old Dominion University, Norfolk, VA, USA, maudette@odu.edu
• Jerzy W. Rozenblit, University of Arizona, Tucson, AZ, USA, jerzyr@arizona.edu

The past two decades have brought about a dramatic increase in the deployment of simulation-based techniques in medicine, healthcare, and human performance models. Simulation scenarios are used extensively for training of medical personnel, students, first responders, and emergency response coordinators. Rapid advances in computer technologies, biomedical engineering, and systems engineering drive the development of cyber-physical systems that serve as simulation-based training platforms. Discrete-event and agent-based models are applied to representing population-based scenarios ranging from clinics to geographical epidemiology scenarios and asking what-if questions for improved outcomes. Physiological processes are modeled and discretized through coupled equations, both in isolation and in integrative physiology contexts. Increasingly, there is also an interest in modeling these processes at several scales, spanning the molecular, to cellular, to tissue and organ-wide scales. However, it is clear that methodological and theoretical foundations need to be strengthened to provide integrated, connected, and cross-cutting solutions for modeling and simulation in medicine, healthcare and human performance optimization. Thus, this meeting will attempt to “connect” researchers, developers, and medical practitioners to define unifying themes conducive to such solutions.

The conference will focus on (but is not limited to) the following topical areas:

• Modeling and simulation in medicine: fundamental research.
• Training and education.
• Care delivery, outcomes, and patient’s safety.
• Robotics and its applications in training and “in vivo”.
• Life-critical systems.
• Systems integration: “connected health”.
• Cybersecurity and healthcare.
• Human performance and ergonomics models.
• Discrete-event and agent-based approaches to healthcare.
• Physiological modeling, from single-system to integrative approaches.
• Multi-scale modeling and simulation in medicine.
• Descriptive anatomical modeling for medical simulation.

Papers are solicited to address the above and related areas with focus on both the underlying methodological and theoretical foundations and practical applications.

Track chairs

• Raju Hasti, vhasti@ucf.edu 
• Dominique Blouin, dominique.blouin@telecom-paris.fr

Standing at the center of climate change, sustainability is the greatest challenge and opportunity of this century. A new generation of sustainable systems will incorporate increasingly sophisticated sensing, control, and communication technologies that maintain or improve performance while using smart management to consume less energy and material. The new capabilities created by these “smart” systems have the potential to radically transform our economy. At the same time, smart systems necessarily include complex software that must be cost-effective and perform reliably while overseeing critical tasks.

Modeling and Simulation (M&S) plays an indispensable role in achieving the simultaneous goals of reliability and affordability by providing virtual venues in which to explore requirements, test new materials and physical instruments, develop new algorithms, and perform software testing. This track invites papers describing novel uses of modeling and simulation to create and demonstrate systems that strive towards smart energy management and a sustainable future. We welcome collaborative works with different and disjoint disciplines such as computer and data sciences, energy, applied math, or environmental sciences.

Topics of interest include, but are not limited to:

• Decision making for sustainability and energy management.
• Environmental and emerging simulation challenges of sustainable systems.
• Building energy systems, including HVAC and energy management systems.
• Smart power grids and micro-grids.
• Energy-efficient cloud computing.
• Internet of Things energy consumption.
• Sustainable cities.
• Carbon emission mitigation strategies.
• New or more efficient forms of power generation.
• ML applications for sustainability concerns.
• Twin city sustainability.

Track chairs

• Roger Azevedo, Roger.Azevedo@ucf.edu
• Omar Ashour, oma110@psu.edu

The SET track is seeking submissions for papers, panels, and workshops related to the following two areas:

Simulation Education: This area focuses on teaching and learning simulation in engineering, sciences, social sciences, or any other discipline where simulation techniques are used in traditional or online settings. We welcome submissions that discuss and share pedagogical models, best practices, lessons learned, program/course projects, tools, case studies, and other resources for training the next generation of simulation experts.

Simulation-Based Learning (SBL): SBL refers to the use of simulation models and tools to enrich teaching and learning. SBL offers a wide range of opportunities for experiential learning and to practice critical thinking, problem-solving, and decision-making. Research shows that SBL is among the most effective ways to learn complex skills across different domains as it enables knowledge application in a virtual yet realistic environment.  Moreover, SBL educational experiences can be made available to geographically dispersed students in support of remote and online learning. All learning situations are of interest (formal/informal, in-person/distance learning, K-12, Higher Education, Professional Training, Continuing Education, etc.)

We encourage contributions that explore emerging trends in both Simulation Education and SBL, highlighting the potential of these tools to reshape education in the years ahead. Submissions from educators, academic researchers, industry professionals, instructional designers, educational technologists, and interdisciplinary teams are welcome, as we seek to uncover the full potential of simulation in transforming educational practices.

Topics of interest include, but are not limited to:

• Implementation and assessment of SBL in courses from any domain (engineering, sciences, social sciences, etc.).
• Problem-/project-based, experiential, and collaborative learning via SBL.
• Skill development and workforce training via SBL.
• SBL in online, in-person, and blended learning models.
• Immersive simulated learning environments (augmented, virtual, and mixed reality, immersive game-based learning).
• Comparative studies on the effectiveness of SBL vs other teaching and learning methods.
• Learning analytics in SBL.

Track chairs

• Dilshan Ossen, dilshan_ossen@ku.edu
• Soheil Sabri, soheil.sabri@ucf.edu

Website

We invite you to submit your original research to SimAUD 2026, as part of ANNSIM 2026, where we gather thought leaders in simulation, architecture, and urban design. SimAUD provides a unique platform for researchers, practitioners, and innovators to explore and advance the use of computational tools and simulation in addressing the challenges of modern urbanization and sustainable design. As buildings account for a substantial share of global energy consumption and greenhouse gas emissions, there is an urgent need for scalable, data-driven approaches to achieve climate-resilient, net-zero, and occupant-centric environments.

This year, we especially encourage submissions that explore AI’s potential in transforming architecture and urbanism. Artificial intelligence—through techniques like generative design, predictive modeling, digital twins, and automated construction—promises to enhance every phase of design, construction, and building lifecycle management, unlocking efficiencies and insights that were previously unattainable. Research focused on these technologies and their applications to climate adaptation, occupant behavior, and energy optimization will be critical to advancing sustainable, responsive environments.

SimAUD welcomes a broad range of topics that address the application of simulation and computation in architecture and urban design, particularly those that incorporate emerging technologies and interdisciplinary methods. This year’s topics of interest include:

• ⁠Simulation, Data-Driven, and Generative Design for Sustainability
• ⁠Whole Building and Urban-Scale Energy Simulation
• ⁠Net-Zero Building Systems and Energy Resilience
• ⁠Multidisciplinary Design Optimization
• ⁠Occupant Behavior Modeling and Human-Centric Design
• ⁠Thermal Comfort, Air Quality, and Occupant Health
• ⁠Advanced Lighting, Daylighting, and Acoustics Simulation
• ⁠Microclimate, Airflow, and Urban Heat Island Modeling
• ⁠Digital Twins and Predictive Maintenance for Smart Buildings
• ⁠Interactive Environments, Responsive Facades, and Biophilic Design
• ⁠Robotic Fabrication, Material Performance, and Structural Simulation
• ⁠Immersive Technologies (AR/VR) in Design Visualization and Collaboration

We encourage submissions from diverse disciplinary perspectives and across various project scales, from individual buildings to entire urban ecosystems. All accepted papers will be published and presented during the conference, contributing to a growing body of knowledge and fostering innovation in sustainable and resilient urban design.

Track chairs

• Gabriel Wainer, Carleton University, Ottawa, Canada, gwainer@sce.carleton.ca
• Paolo Bocciarelli, University of Rome Tor Vergata, Rome, Italy, paolo.bocciarelli@uniroma2.it

The TMS Track serves as a dynamic platform for showcasing the latest advancements in the Theory and Foundations of Modeling and Simulation. Emphasizing the breadth of concepts, methodologies, practices, and toolkits in the field, the TMS Track invites submissions of unpublished papers that explore these topics and beyond, aiming to enrich and expand the theoretical and foundational aspects of Modeling and Simulation. This initiative seeks contributions that enhance our understanding and development of systems in the fields of networks and computers, cyber-physical systems, applications in nature (physics, chemistry, biology), as well as social applications.

Selected topics include:

• Modeling & Simulation Formalisms (Actors, DEVS, Petri nets, Statecharts, etc.)
• Multi-formalism Modeling, Hybrid Modeling Languages, Multi-Modal Modeling
• Multi-Resolution/Multi-Scale Modeling, Multi-Paradigm/Multi-Domain Modeling,
• Model Checking, Formalism-Based Model Debugging, Model Transformation
• Parallel, Distributed, Real-Time, Cloud-Based, and Interactive Simulation
• Modular Hybrid, Spatially Distributed, and Ultra Large-Scale Systems
• Co-simulation, Interoperability, Simulation Languages, Numerical Solvers
• Embedded, IoT, and Fog Computing Modeling and Simulation Software
• Theory for Modeling Cyber-Physical Systems and Digital Twins
• Theory and Methodologies for Business Process M&S (Human-in-the-loop, resources modeling, processes optimization, etc.)
• Model Development and Simulation Visualization Tools
• Model Libraries, Repositories, and Data Formats
• Data-driven simulation inferencing and learning