Title: Safe autonomy within reach: a verified machine learning and control perspective
Abstract: Over the last decade, we have seen impressive progress across all areas of autonomy, including perception, control and learning. At the same time, developing safe and secure cyber-physical systems (CPS) remains a challenging task, as demonstrated by multiple recent accidents involving autonomous vehicles, drones and aircraft. In this talk, I will present an integrated approach to assuring the safety and security of CPS through a combination of offline verification and online monitoring techniques.
For offline assurance, I have developed an approach, called Verisig, for verifying the safety of autonomous systems with neural network controllers. I will present an exhaustive evaluation on a neural-network-controlled (1/10-scale) autonomous racing car, both in terms of verification and experiments on the real platform. In the second part of the talk, I will describe my work on run-time monitoring of system safety, with applications to medical CPS. Specifically, I will present a detector for critical drops in the patient's oxygen content during surgery, with guaranteed performance regardless of varying physiological parameters such as metabolism. The detector is evaluated on real-patient data collected from the Children's Hospital of Philadelphia.
Speaker Bio: Radoslav Ivanov received the B.A. degree in computer science and economics from Colgate University in 2011, and the Ph.D. degree in computer and information science from the University of Pennsylvania in 2017. He is currently an assistant Professor at Rensselaer Polytechnic Institute. His research interests are broadly in the field of safe and secure autonomy, with a focus on verified machine learning, control theory and cyber-physical security. The natural application domains of his work are automotive and medical cyber-physical systems.
Date and Time:
Thursday Sept. 8th, 2022
1:00 PM - 2:30 PM (EDT)
View Recording here