[CSEE Talk] talk: Learning and Optimization for Complex Dynamic Networks, 11:45a Tue 3/11

[Tim Finin]

              Computer Science and Electrical Engineering
                University of Maryland, Baltimore County

        Learning and Optimization for Complex Dynamic Networks:
   The Cases of Future Power Systems and Cognitive Wireless Networks

               Dr. Seung-Jun Kim, University of Minnesota

           11:45-12:45 Tuesday, 11 March 2014, ITE325b, UMBC


With enormous growth in sensing and communication capabilities as well
as processing power to analyze collected data, we are witnessing
exciting opportunities in diverse disciplines to study complex
interactions of networked entities. The overarching theme is to
explore cutting-edge computational intelligence tools from signal
processing, machine learning, optimization, and control to make sense
of amassed data and exploit complex interactions to make significant
real-world impacts. In this talk, I will make cases for two prime
examples, namely, future power systems and cognitive wireless
networks. The role of contemporary tools including online learning,
sparse and low-dimensional models, distributed and robust algorithms,
will be emphasized.


Seung-Jun Kim received his B.S. and M.S. degrees from Seoul National
University in Seoul, Korea in 1996 and 1998, respectively, and his
Ph.D. from the University of California at Santa Barbara in 2005, all
in electrical engineering. From 2005 to 2008, he worked for NEC
Laboratories America in Princeton, New Jersey, as a Research Staff
Member. He is currently with the Department of Electrical and Computer
Engineering and the Digital Technology Center at the University of
Minnesota, where he is a Research Associate Professor and a Research
Associate. His research interests lie in applying signal processing,
optimization, and machine learning techniques to various application
domains including wireless communication and networking and smart
power grids.

Host: Tinoosh Mohsenin, tinoosh at umbc.edu

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