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![]() In This Issue March 2010 Vol. 8, Issue 1 Bovik Receives IEEE Signal Processing Society’s Best Paper Award for 2009 Prof. Vishwanath Organizes “From Idea to Intellectual Property” Class Prof. Sujay Sanghavi receives NSF CAREER Award WNCG Founder runs in Austin Marathon Prof. Rappaport’s Group Attends IEEE International Solid-State Circuits Conference Prof. Shakkottai Organizes Workshop on Frontiers of Controls, Games and Network Science News Station Films Segment on Rappaport's Research ECE Staff Member Elected to UT Staff Council
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Prof. Sujay Sanghavi receives NSF CAREER Award ![]() Sujay Sanghavi, who joined WNCG in July 2009 as an Assistant Professor, received the National Science Foundation CAREER award in Jan 2010. The CAREER program represents "the National Science Foundation's most prestigious awards in support of the early career- development activities of those teacher-scholars who most effectively integrate research and education,” according to the NSF. Prof. Sanghavi's award was funded at $425,000 as a single principal-investigator grant for a duration of five years and enables research at the intersection of two central challenges in modern information systems: the distributed control and optimization of large-scale networks and the tractable interpretation of noisy and high-dimensional data. In particular, it develops a common algorithmic framework, based on Markov Random Fields from statistics, that enables the easy migration of ideas across several domains where networks arise: communications, sociology, biology etc. Several projects representative of this cross-network view are already active in Prof. Sanghavi's group. One example is mining call log data and doing social network analysis to increase the value of cellular phone networks to users (see related article in this publication). Another example involves a general new method to identify dense sub-clusters in networks, which enables capacity and reliability planning in communication networks, component placement in VLSI systems and subgroup identification in social networks.
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