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Colloquium - Zuliani

Verification of Stochastic Systems by Statistical Model Checking
Carnegie Mellon University
3/6/2012
3:30pm-4:30pm

Statistical model checking is a simulation-based approach for verifying temporal logic properties of complex stochastic systems. Traditional model checking techniques work by searching efficiently the entire state space of the system. However, many interesting systems (e.g., cyber-physical systems) have exceedingly large, or even infinite, state spaces. This makes techniques based on exhaustive search unfeasible. Statistical model checking is instead based on sampling and system simulation, and thereby scales better with system size. We present a statistical model checking approach based on Bayesian statistics, and we apply it to biological pathway models and embedded systems. We conclude by discussing the strength and weaknesses of the approach and possible directions for future research.

Dr. Paolo Zuliani is the Technical Coordinator of the NSF project "CMACS - Computational Modeling and Analysis for Complex Systems" at the Department of Computer Science, Carnegie Mellon University. Dr. Zuliani's expertise lies largely in formal methods for reasoning about computing systems, with an emphasis on probabilistic and quantum systems. In the past few years he has become interested in applied formal methods for stochastic systems and model checking. He is in particular interested in the verification of embedded systems and biological systems. Dr. Zuliani received his Laurea degree in computer science from Università degli Studi di Milano, Italy, and his DPhil in computer science from the University of Oxford, UK. After receiving his DPhil, he taught at the University of Bolzano, Italy, for two years. He was then awarded a Marie Curie Fellowship from the European Commission, which he spent at Princeton University and Oxford.

This talk is sponsored by the Department of Electrical, Computer and Energy Engineering.

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