Sayan Mitra

Sayan Mitra is a Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign, with an affiliate appointment in Computer Science since 2018. His research focuses on formal methods for cyber-physical systems, particularly safety verification for autonomous systems. He directs a research laboratory at the Coordinated Science Lab (266 CSL) with multiple PhD students and collaborators.

Dr. Mitra received his Ph.D. from MIT in 2007 under Nancy Lynch, with a thesis titled "A Verification Framework for Hybrid Systems." He completed his MSc at the Indian Institute of Science (2001) and his BE at Jadavpur University (1999).

His research interests span Control Theory, Formal Methods, AI and Autonomy, Cyber-Physical Systems, and Embedded Systems. He has made significant contributions to verification techniques for hybrid systems, runtime assurance for learning-enabled controllers, and symmetry-based abstractions that improve verification efficiency. His work addresses critical safety challenges in autonomous vehicles, satellite systems, and multi-agent robotics.

Analysis of his recent publications shows a strong trend toward practical verification methods for real-world autonomous systems, particularly focusing on integrating machine learning components while maintaining safety guarantees. His work increasingly emphasizes runtime assurance techniques, symmetry-based verification improvements, and practical tools for industry adoption.

• National Science Foundation's Faculty Early Career Development (CAREER) Award (2011)
• Air-Force Office of Scientific Research (AFOSR) Young Investigator Research Award (2012)
• College of Engineering Dean's award for excellence in research (2018)
• ACM Doctoral Dissertation Award for advisee Chuchu Fan (2021)
• HSCC Keynote lecture (2024)

Dr. Mitra has advised numerous PhD students including Chuchu Fan (winner of ACM Doctoral Dissertation Award 2021) and Hussein Sibai (gold prize at ACM SIGBED Student Research Competition 2021). His research has been supported by multiple NSF grants, AFOSR funding, and industry collaborations. He leads the development of verification tools including Verse and Ray for multi-agent hybrid system analysis. His laboratory focuses on bridging theoretical verification methods with practical applications in autonomous systems, particularly addressing the safety challenges of integrating machine learning components into safety-critical control systems.