Personalizing Health in an Impersonal World:
Design and Analysis for Safe Autonomous Medical Systems
Modern computing systems that interact with patients and clinicians, commonly referred to as medical cyber-physical systems (MCPS), are safety-critical embedded systems that feature tight coupling between communication and computation used to control complex, dynamic, and uncertain physical/physiological plants. Autonomous MCPS additionally incorporate components whose behavior is driven by “background knowledge” acquired and updated through a “learning process”. While empirical medical data is often a significant source of this background knowledge, it can also be limited, sparse, or “thin” due to small sample sizes, dataset shifts, anomalies, inter/intra-patient variability, and a limited understanding of the data generation process itself. Consequently, providing safety guarantees and predictable performance for autonomous MCPS in the presence of thin data is challenging. In this talk, I will present some of my recent work on techniques and tools for the design and analysis of safe and secure autonomous MCPS with thin data. Specifically, in the context of autonomous medical systems, I will present: (i) the Verisig tool for formal verification of closed-loop learning-enabled systems; and (ii) resilient linear regression for the internet-of-(medical)-things. Real-world case study evaluations for type I diabetes and the artificial pancreas, as well as autonomous vehicles, illustrate the utility of my recent work and give light to future research challenges in both medical and non-medical domains.
James Weimer is a Research Assistant Professor in the Department of Computer and Information Science at the University of Pennsylvania and in the Department of Biomedical and Health Informatics at the Children’s Hospital of Philadelphia. His research interests include the design and analysis of cyber-physical systems with application to learning-enabled/autonomous medical systems, safe autonomy, and cyber-physical security. James holds a Ph.D. degree in Electrical and Computer Engineering from Carnegie Mellon University and prior to joining Penn held a Postdoctoral Researcher position at the KTH Royal Institute of Technology. He serves as an associate editor for the ACM Transactions on Cyber-Physical Systems and the ACM Transactions on Computing for Healthcare. Additionally, he is the Program co-Chair for the International Conference on Cyber-Physical Systems (ICCPS) 2020 as part of CPS week. In response to the COVID-19 pandemic, he co-leads the emergency ventilation rapid response task force for the University of Pennsylvania in direct support of its six hospital network.