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Predictable Autonomy for Cyber-Physical Systems
Stanley Bak
IRB 4105
Friday, February 21, 2020, 11:00 am-12:00 pm Calendar
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Abstract
Cyber-physical systems combine complex physics with complex software. Although these systems offer significant potential in fields such as smart grid design, autonomous robotics and medical systems, verification of CPS designs remains challenging. Model-based design permits simulations to be used to explore potential system behaviors, but individual simulations do not provide full coverage of what the system can do. In particular, simulations cannot guarantee the absence of unsafe behaviors, which is unsettling as many CPS are safety-critical systems.

The goal of set-based analysis methods is to explore a system's behaviors using sets of states, rather than individual states. The usual downside of this approach is that set-based analysis methods are limited in scalability, working only for very small models. This talk describes our recent process on improving the scalability of set-based methods, where the states are in some Euclidean space. We describe linear star sets, a new spatial data structure that we used to verify properties about linear time-invariant hybrid automata with many (up to one billion!) coupled continuous state variables. Lastly, we discuss using linear star sets to perform set-based input/output verification of neural networks.
Bio
Stanley Bak received a Bachelor's degree in Computer Science from Rensselaer Polytechnic Institute (RPI) in 2007 (summa cum laude), and a Master's degree in Computer Science from the University of Illinois at Urbana-Champaign (UIUC) in 2009. He completed his PhD from the Department of Computer Science at UIUC in 2013. He received the Founders Award of Excellence for his undergraduate research at RPI in 2004, the Debra and Ira Cohen Graduate Fellowship from UIUC twice, in 2008 and 2009, and was awarded the Science, Mathematics and Research for Transformation (SMART) Scholarship from 2009 to 2013. From 2013 to 2018, Stanley was a Research Computer Scientist at the US Air Force Research Lab (AFRL), both in the Information Directorate in Rome, NY, and in the Aerospace Systems Directorate in Dayton, OH. He has performed teaching as an Adjunct Professor at Georgetown University, and currently helps run Safe Sky Analytics, a research consulting company investigating verification methods for autonomous systems.
This talk is organized by Richa Mathur