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Dear All,

The department of computer science invites you to a seminar on "Safety Verification of AI-enabled Cyber-Physical Systems"

Abstract: AI-based components are increasingly integrated into autonomous and cyber-physical systems (CPS), replacing traditional modules in control and perception. These integrations have led to significant advances in safety-critical domains such as aerospace, automotive systems, and robotics. At the same time, the increased adaptability and complexity of AI-enabled components introduce new safety challenges, as failures in such systems can lead to catastrophic consequences. To address these challenges, formal verification is emerging as a powerful framework for providing guarantees on the correctness and safety of such systems.

In this talk, we focus on safety verification of AI-enabled CPS along two complementary directions.

First, we address the continuously evolving nature of neural network controllers, which are frequently retrained or updated to improve performance. We introduce an approximate conformance framework that enables safety guarantees of a previously verified network to be transferred to its retrained variants without re-verifying the entire closed-loop system from scratch.
Second, we consider safety verification of anytime perception-based CPS. Anytime sensors are being introduced to offer flexibility in latency and accuracy, unlike traditional sensors with fixed performance. Such variations in sensing performance can lead to mission-critical failures. We address this challenge by developing efficient reachable-set computation algorithms for closed-loop systems with anytime sensors and neural network controllers using the star set data structure and designing new algorithms for some star set operations. 

About the Speaker: Lipsy Gupta is a Research Assistant Professor in the Department of Computer Science at Kansas State University. She was previously a Postdoctoral Fellow at Kansas State University and at the University of Missouri–Columbia. Her research focuses on developing practical formal methods for scalable analysis of AI-enabled autonomous systems, providing mathematical guarantees for their safety, reliability, and privacy, with publications at ICRA, EMSOFT, CDC, and IEEE TCAD. She has been recognized with several awards at Kansas State University, including the Distinguished Research Award and the Excellence in Research Award. She holds a Ph.D. in Mathematics from the Indian Institute of Technology Delhi, where her work centered on topology of metric spaces.

We look forward to your active participation.

Regards,

Department of Computer Science