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Faculty News
Dr. Xulong Tang, an associate professor in the Department of Computer Science, is participating in a five-year $5 million NSF ExpandQISE Track 2 Grant. The project, titled “ExpandQISE: URI-PQI Collaboration - Application of Quantum Fundamentals to Advance Research and Workforce Development,” is led by the University of Rhode Island in collaboration with the Pittsburgh Quantum Institute, Carnegie Mellon University, and the University of Pittsburgh.
Dr. Ryan Shi, assistant professor in the Department of Computer Science and Intelligent Systems Program, recently received a Google Academic Research Award to address these issues and better reach farmers, particularly smallholder farmers in the global south.
Dr. Xiaowei Jia (assistant professor) received an Early Career Investigator Grant from NASA's Earth Science Division for his project “Towards Generalizable, Fair, and Knowledge Guided Machine Learning for Monitoring Earth Systems.”
Student News
Senior computer science Student Griffin J. Hurt has been named a 2024 Graduate Research Fellowship Program (GRFP) scholar.
Two students from the School of Computing and Information (SCI) Department of Computer Science have been recognized for their undergraduate research by the Computing Research Association (CRA)!
Last month, 33 students (18 in person and 15 virtually) from the School of Computing and Information (SCI) attended the Grace Hopper Conference (GHC) in Orlando, FL.
Colloquium Talks
This talk will discuss both the method and data foundations to scale AI models for large-scale geospatial applications and science questions, covering new frameworks for spatially-explicit learning, knowledge-guided learning, task-aligned pretraining, as well as new benchmark datasets and data generation methods.
Curating models is time-consuming, so I have developed AI tools to help scholars build models of the hidden structure of their digital archives. This talk features a lot of fine art and it is open to anyone interested in AI-enhanced scholarship in the arts and humanities.
By unifying LLMs with agent-based modeling, this talk offers a forward-looking methodology for analyzing digital influence, testing intervention strategies, and understanding how automated bot agents can shape the cognitive terrain of online societies.
