Distinguished Lecture Series in Honor of the 50th Anniversary of the Department. Seminar: Autonomous Systems: How to address the Dilemma between Autonomy and Safety

Abstract

    The need for more autonomy in many systems (e.g., automotive, aerospace) leads to increasingly complex systems that are becoming harder to verify and certify. This problem is compounded by the rising use of AI to enable such autonomy in many critical functions. Such a situation has a significant impact on software development practice and makes it particularly difficult to assess risks and meet industry standards. This talk will focus on automated techniques, relying on various AI disciplines, to enable the testing and risk analysis of such systems, in ways that are practical and scalable. The talk will report and reflect on various research projects carried out in collaboration with the automotive and satellite industries.

Bio

Lionel C. Briand is a professor of software engineering and has shared appointments between (1) The University of Ottawa, Canada, and (2) The SnT Center for Security, Reliability, and Trust, University of Luxembourg. In collaboration with colleagues, over 25 years, he has run many collaborative research projects with companies in the automotive, satellite, aerospace, energy, financial, and legal domains. Lionel was elevated to the grades of IEEE Fellow and ACM Fellow for his work on software testing and verification. He was granted the IEEE Computer Society Harlan Mills award, the ACM SIGSOFT outstanding research award, and the IEEE Reliability Society engineer-of-the-year award, respectively in 2012, 2022, and 2013. He received an ERC Advanced grant in 2016 — on the topic of modeling and testing cyber-physical systems — which is the most prestigious individual research award in the European Union. He currently holds a Canada Research Chair (Tier 1) on "Intelligent Software Dependability and Compliance". His research interests include: software testing and verification, applications of AI in software engineering, model-driven software development, requirements engineering, and empirical software engineering.