Trustworthy AI-enabled Autonomous Systems Lab

Pavithra Prabhakar is a Professor in the Department of Computer Science and the Cleve Moler and MathWorks Endowed Chair in Mathematical and Engineering Software at the University of New Mexico. Prior to joining UNM, she was a Professor of Computer Science and the Peggy and Gary Edwards Chair in Engineering at Kansas State University. She earned her Ph.D. in Computer Science and an M.S. in Applied Mathematics from the University of Illinois Urbana–Champaign, followed by a CMI Postdoctoral Fellowship at the California Institute of Technology. Prabhakar’s research focuses on formal methods for AI-enabled autonomous, cyber-physical, and robotic systems, with applications in aerospace, automotive, and agricultural automation. She has authored over 100 peer-reviewed publications and has received numerous honors, including a Marie Curie Career Integration Grant from the EU, NSF CAREER Award, ONR Young Investigator Award, NITW Distinguished Young Alumnus Award, Amazon Research Award, CRA Future Leader recognition, and a 2025 Early Career Academic Achievement Alumni Award from UIUC. More recently, she served as a Program Director at the National Science Foundation (NSF) in the CISE Directorate, where she led a portfolio of over 200 research projects with a total budget exceeding $100 million, spanning Formal Methods, Cyber-Physical Systems, Robotics, and Artificial Intelligence.

Lipsy is a Research Assistant Professor in the TRAITSS Lab. Her research lies at the intersection of Formal Verification, Artificial Intelligence, and Cyber-Physical Systems (CPS), where she aims to develop practical formal methods for scalable analysis of AI-enabled autonomous systems and tackle the safety and reliability challenges by providing mathematical guarantees. She was previously a Postdoctoral Fellow at Kansas State University and at the University of Missouri–Columbia. Her academic background is in Mathematics. She completed her Ph.D. in Mathematics at IIT Delhi, where she studied the topology of metric spaces.

Habeeb P. is a Postdoctoral Fellow in the Department of Computer Science at Kansas State University. He completed his Ph.D. in Computer Science in 2025 at the Indian Institute of Science (IISc), Bangalore, where he also earned his M.Tech (Research) in Computer Science. His research lies at the intersection of formal methods, program verification, and the safety of AI-enabled systems, with a particular focus on neural network verification, cyber-physical systems, and programming languages. He is broadly interested in developing rigorous techniques to ensure the reliability, security, and correctness of safety-critical and AI-driven systems.

Hassan is a Ph.D. student in Computer Science with a background in both software development and robotic engineering. He earned his Master of Science degree from the University of Isfahan, where he specialized in optimization, computer vision, and conducted research in natural language processing. His current research focuses on reinforcement learning and optimal control, with an emphasis on applying formal verification methods to autonomous robotic systems. He also works extensively with ROS and robot simulation platforms to study reliable and efficient decision-making in complex environments.