most significant bits
newsletter of uw computer science & engineering
volume 19, number 2, winter 2010
university of washington
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 home CSE Home     Winter 2010 MSB    MSB Archive    Contact Info 
Distinguished Lecturer Series   Simonyi in Space   Myhrvold in the Kitchen   More Familiar Terrain Chair's message New Faculty Additions   Su-In Lee   Anup Rao   Luke Zettlemoyer News   Girl Geek Dinner   Datagrams   CSE Alum in NYTimes Kindle DX Pilot Program Awards   TR35 Winners   CRA Undergrads
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About MSB

MSB is a twice yearly publication of UW CSE supported by the Industrial Affiliates Program.

Editor: Kay Beck-Benton
Contributors: Ed Lazowska, Hank Levy, Sandy Marvinney
Photo credits: Bruce Hemingway, Rod Prieto

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New Faculty Additions

Su-in Lee

Su-In Lee joined the faculty in Computer Science & Engineering and Genome Sciences in January 2010. She received her Ph.D. from Stanford University in January 2009 and most recently was a visiting assistant professor at Carnegie Mellon University.

Lee’s research focuses on computational methods and machine-learning techniques for understanding the genetic basis for complex traits. Humans differ in many phenotypes such as weight, hair color, and, more importantly, disease susceptibility. These phenotypes are largely determined by each individual’s specific genotype, stored in the 3.2 billion pairs of his or her DNA sequence. Lee’s long-term research goal is to develop interdisciplinary approaches combining computer science and biology to decipher the genetic code from various types of genomic data. For more information on Su-In and her research, please see:

Anup Rao

Anup Rao joined the faculty in January 2010. He received his Ph.D. from the University of Texas at Austin and recently finished two and a half years as a post doc, first at the Institute for Advanced Study in Princeton, NJ, and then at Princeton University.

Rao’s research aims to understand some of the foundational questions of computer science. His past work has focused on the study of pseudo randomness, lower bounds and approximation algorithms, efficient ways to reduce the dependence of computer science solutions on pure randomness, and on improving understanding of optimization problems for which it is hard to approximate answers. Rao’s theoretical research has achieved success in answering the questions “To what extent is the use of randomness necessary to computer science?” and “How can we amplify the hardness of computational problems?” These kinds of questions can sometimes lead to strange and unexpected revelations — for example, a recent sequence of work that he was involved with led to the discovery of the most economical shape for soap bubbles. For more information on Anup and his research, please see:

Luke Zettlemoyer

Luke Zettlemoyer joins the faculty in July 2010, after he completes a post doc at the University of Edinburgh. He received his Ph.D. from MIT.

Zettlemoyer’s research focus is artificial intelligence. He has worked on problems in natural language processing, machine learning, and decision making under uncertainty. One goal of this work is to build automated systems that can have natural conversations with human users. He has worked on a number of aspects of this problem, including (1) grammar induction techniques for learning to automatically convert sentences to logical representations of their underlying meaning; (2) methods for efficiently reasoning about nested beliefs ; and (3) algorithms for model learning and decision making in large, structured environments. Zettlemoyer is generally interested in building systems that recover and make use of representations of the meaning of natural language text. For more information on Luke and his research, please see:

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