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Talks & Seminars
Title: Formal Methods for Lab-Based MOOCs: Cyber-Physical Systems and Beyond
Sanjit Seshia, Univ. California, Berkeley, University of California, Berkeley.
Date & Time: October 20, 2014 11:30
Venue: Conference Room, CSE Office
Abstract:
The advent of massive open online courses (MOOCs) has placed a renewed focus on the development and use of computational aids for teaching and learning. Lab-based courses, such as those in embedded systems and robotics, are particularly challenging. In this talk, I will describe our experience, spanning both research and teaching, in designing a MOOC version of the introductory undergraduate course on embedded systems at UC Berkeley and the associated technology. A key component of this MOOC was the "virtual laboratory", where students perform lab exercises using virtual lab software we created with built-in automatic grading and feedback based on formal methods. I will describe the design and evaluation of CPSGrader, the auto-grading system, summarize results from the MOOC offering on edX, and sketch directions for future work. This talk describes joint work with several collaborators including Alexandre Donze, Jeff Jensen, Garvit Juniwal, and Edward Lee.
Speaker Profile:
Sanjit A. Seshia is an Associate Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He received an M.S. and Ph.D. in Computer Science from Carnegie Mellon University, and a B.Tech. in Computer Science and Engineering from the Indian Institute of Technology, Bombay. His research interests are in dependable computing and computational logic, with a current focus on applying automated formal methods to problems in cyber-physical systems, computer security, and synthetic biology. His Ph.D. thesis work on the UCLID verifier and decision procedure helped pioneer the area of satisfiability modulo theories (SMT) and SMT-based verification. He is co-author of a widely-used textbook on embedded systems. His awards and honors include a Presidential Early Career Award for Scientists and Engineers (PECASE) from the White House, an Alfred P. Sloan Research Fellowship, the Prof. R. Narasimhan Award from TIFR, and the School of Computer Science Distinguished Dissertation Award at Carnegie Mellon University.
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