Data Science
[PAST EVENT] CS Distinguished Talk: Sebastian Elbaum
Access & Features
- Open to the public
Title: Analyzing the Long-Tail Distribution of Autonomous Systems
Abstract:
The proliferation of autonomous systems exposes the hidden dangers and potential consequences of their failures. These failures expose limitations in current analysis techniques, struggling with the long-tail distribution of inputs exercising these systems, which is further compounded by the integration of real-world semantics and machine learning components. In this talk, I will provide an overview of the systems and the spectrum of properties they aim to achieve, ranging from robustness to adherence to policy. Finally, I will present a suite of techniques tackling these analysis challenges, encompassing methods from DNN verification to testing and analysis with physical-semantics.
Bio:
Sebastian Elbaum is a Professor in the Department of Computer Science at the University of Virginia where he co-leads the Lab for Engineering Safe Software (LESS Lab). His research aims to build dependable systems through domain-specific analysis techniques. He is the recipient of an NSF Career Award, an IBM Innovation Award, a Google Faculty Research Award, an FSE Test of Time Award, five ACM SigSoft Distinguished Paper Awards, and multiple best paper awards. He regularly serves in program committees at the top software engineering and robotic conferences, and has served as Program Co-Chair for ISSTA07, ESEM08, and ICSE2015, and as Steering Committee Chair for ICSE. His latest work focuses on robotic systems with learned components. He is an ACM Fellow and an IEEE Fellow.
Sponsored by: Computer Science Deparment
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