3:00p.m., Tuesday, 10rd Nov. 2020

Venue:

Tencent Meeting ID: 483808287

Password: 312312

Topic:

By now we know that neural networks are stubbornly brittle and easier to attack than traditional software systems. The question is then: how do we make sure the neural networks do not lead to safety violation on safety critical systems such as self-driving cars? One idea is to automatically repair a given neural network based on a given safety requirement. In this talk, I will present our ongoing efforts on developing verification-based repairing techniques for neural networks.

Lecturer:

SUN, Jun is currently an associate professor at Singapore Management University (SMU). He received Bachelor and PhD degrees in computing science from National University of Singapore (NUS) in 2002 and 2006. In 2007, he received the prestigious LEE KUAN YEW postdoctoral fellowship. He has been a faculty member since 2010. He was a visiting scholar at MIT from 2011-2012. Jun's research interests include software engineering, formal methods, program analysis and cyber-security. He is the co-founder of the PAT model checker. To this date, he has more than 200 journal articles or peer-reviewed conference papers, many of which are published at top-tier venues. His academic papers have won many international conference awards, and he is also the organizer of many international conferences.

Organizer:

Office of International Cooperation & College of Intelligence and Computing,

Tianjin University