harbir antil, george mason university

biography

Harbir Antil is Professor of Mathematics and Founding Director of the Center for Mathematics and Artificial Intelligence (CMAI) at George Mason University. His research lies at the intersection of optimization, partial differential equations, inverse problems, uncertainty quantification, and scientific computing, with applications to computational imaging, sensing, digital twins, and physics-informed artificial intelligence. His work develops mathematical and algorithmic foundations for PDE-constrained and nonsmooth optimization, risk-aware decision-making, nonlocal models, and reduced-order and hybrid physics–AI methods. Recent projects connect these ideas to high-fidelity digital twins, structural health monitoring, biomedical flow modeling, neuromorphic and event-based imaging, and real-time decision-making from sparse or indirect measurements. Dr. Antil’s research is broadly supported by the NSF, DOE, DARPA, ONR, AFOSR, DTRA, and industry partners including Simula Labs. His publications appear in leading journals in applied mathematics, scientific computing, and optimization, and his work has been featured in the New York Times and NSF Research Highlights. He is a member of the Intelligence Science and Technology Experts Group at the National Academies of Sciences, Engineering, and Medicine. He serves as Associate Editor for the SIAM Journal on Scientific Computing and the SIAM Review Research Spotlights section, and is President of the SIAM DC–Maryland–Virginia Section. Beyond academia, his optimization and digital twin frameworks have influenced applications in structural health monitoring, biomedical systems, and computational imaging, including algorithms deployed aboard the International Space Station. He was invited to deliver a plenary lecture at the Joint Mathematics Meetings 2026.

davide scaramuzza, university of zurich

BIOGRAPHY

Davide Scaramuzza is a Professor of Robotics and Perception at the University of Zurich. He did his Ph.D. at ETH Zurich, a postdoc at the University of Pennsylvania, and was a visiting professor at Stanford University and NASA Jet Propulsion Laboratory. His research focuses on autonomous, agile navigation of mobile robots using standard and event-based cameras. He made fundamental contributions to visual-inertial state estimation, autonomous vision-based agile navigation of micro flying robots, and low-latency perception with event cameras, which were transferred to many products, from drones to automobiles, cameras, AR/VR headsets, and mobile devices. He pioneered autonomous, vision-based navigation of drones, which inspired the algorithm of the NASA Mars helicopter. In 2022, his team demonstrated that an AI-powered drone could outperform the world champions of drone racing. He received several awards, including a IEEE Technical Field Award, the IEEE Fellowship, the IEEE Robotics and Automation Society Early Career Award, a European Research Council Consolidator Grant, a Google Research Award, and many paper awards. In 2015, he co-founded Zurich-Eye, today Meta Zurich, which developed the head-tracking software of the Meta Quest. In 2020, he co-founded SUIND, which builds autonomous drones for precision agriculture. Many aspects of his research have been featured in the media, such as The New York Times, The Guardian, The Economist, and Forbes. He co-authored the book "Introduction to Autonomous Mobile Robots," published by MIT Press, which has sold over 10 thousand copies worldwide and is among the most used textbooks for teaching mobile robotics. He has been consulting the United Nations on disaster response, the Fukushima Action Plan, disarmament, and AI for good.

yu sun, johns hopkins university

BIOGRAPHY

Yu Sun is an Assistant Professor of Electrical and Computer Engineering at Johns Hopkins University, where he directs the Hopkins Computational Imaging Group. He holds joint appointments with the Data Science and Artificial Intelligence Institute (DSAI) and the Center for Imaging Science (CIS). His research is focused on advancing the algorithmic and theoretical foundations of computational imaging, with an emphasis on integrating machine learning techniques to address complex imaging challenges. Sun earned his Ph.D. in Computer Science from Washington University in St. Louis in 2022, where his doctoral dissertation received the Turner Dissertation Award. Before joining Johns Hopkins, he was a Computing, Data, and Society Fellow at the California Institute of Technology. Sun is a recipient of the Rising Star Award from the Conference on Parsimony and Learning. He is an elected member of the IEEE Signal Processing Society's Computational Imaging Technical Committee (CI TC) and serves as a Consulting Associate Editor for the IEEE Open Journal of Signal Processing.

jinwei ye, george mason university

BIOGRAPHY

Jinwei Ye is an associate professor of Computer Science at George Mason University. Before that, she was an assistant professor at Louisiana State University (2017–2021). She received her Ph.D. in Computer Science from the University of Delaware in 2014. She worked with ARL (2014 - 2015) and Canon U.S.A. (2015 - 2017). Her research interests are at the intersection of computational imaging, computer vision, and computer graphics, with focus on geometry and appearance understanding. Her works are largely supported by NSF and ARL. She received the NSF CAREER awards in 2023. She served in the senior program committee and organizing committee for major computational imaging and computer vision conferences, including ICCP, CVPR, ICCV, ECCV and WACV.