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Model-Based Analysis and Design for Complex System Integration

How can we efficiently certify that autonomous vehicles will meet safety and performance requirements in the presence of modeling uncertainties and adversaries? How can we quantify and reduce risks in safety-critical and high-cost applications? How can we guide scientists and engineers to design the most informative next experiment/test? Motivated by these and similar questions, I will present my recent work on developing analytical and computational tools that facilitate model-based analysis and design of complex engineering systems and their integration into the existing infrastructure. The presentation will focus on three complementing research directions: (i) automatic generation of provably correct control protocols for autonomous systems; (ii) quantitative analysis and verification of networked, nonlinear dynamical systems; and (iii) uncertainty quantification in support of predictive science and engineering. I will draw motivating and illustrative examples from aerospace applications, autonomous robots, next generation power networks, and certification in safety-critical applications.

The slides of the presentation can be found at the following URL:

Type of Seminar:
IfA Seminar
Dr. Ufuk Topcu
California Institute of Technology
May 11, 2010   14:15

Physikstrasse 3, K 25
Contact Person:

No downloadable files available.
Biographical Sketch:
Ufuk Topcu is a postdoctoral scholar in Control and Dynamical Systems at the California Institute of Technology. His research focuses on developing analytical and computational tools for the design and verification of and uncertainty quantification for complex engineering systems. He received the Ph.D. in 2008 from the University of California, Berkeley.