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Yahoo! Research
111 W. 40th Street, 17th Floor
New York, NY 10018 (map)
goel AT yahoo-inc DOT com
Tel: 212-571-8149 (work)
Tel: 607-339-9903 (mobile)
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EDUCATION
Research Fellow, Dept. of Mathematics, University of Southern California, 2006 - 2007 Research Fellow, Dept. of Mathematics, Stanford University, 2005 - 2006 PhD in Applied Mathematics, Cornell University, 2005
MS in Computer Science, Cornell University, 2003
BS in Mathematics, University of Chicago, 1999
Hello! I work in the social networks groups at Yahoo! Research. When I'm not doing math I like to relax by playing cello, and learning to play the sitar that I couldn't resist bringing back from India on a recent trip. If you're bored, check out two web projects I've worked on: Quirksome and Friendcast
2006-2007 (USC)
2005-2006 (Stanford University)
2004-2005 (Cornell University)
RESEARCH INTERESTS
- Theoretical and applied probability
- Quantitative analysis of finite Markov chains
- Applied statistics
How many times do you need to shuffle a deck of cards before it is close to random? Intuitively, if you shuffle enough times, the order of the cards shouldn't depend on the initial order of the deck. This intuition was in fact confirmed already in the early twentieth century by Markov and Poincaré. But given 52 cards, exactly how many times do you need to shuffle the deck? 10? 100? 1000? More generally, while classical results show that under mild conditions finite Markov chains converge to equilibrium exponentially fast, those results help little in answering the type of non-asymptotic question posed above.
Much of my research deals with understanding the convergence behavior of finite Markov chains. Recently, I've also become interested in applications of Markov chain theory.
PUBLICATIONS/PREPRINTS
EXPOSITORY/MISCELLANEA
INVITED TALKS
Horseshoes in Multidimensional Scaling (slides)
Probability Seminar, UC-Irvine Department of Mathematics, March 2007
Probability Seminar, USC Department of Mathematics, March 2007
Yahoo! Research Labs, February 2007
Probability Seminar, UCLA Department of Mathematics, February 2007
Respondent-Driven Sampling as Markov Chain Monte Carlo (slides)
Social Networks Symposium, John Jay College, August 2007
USC Department of Mathematics, February 2007
Interpreting Eigenmaps
Georgia Tech Department of Mathematics, April 2006
Shuffling Cards: Estimating Mixing Times for Finite Markov Chains
Colloquium, Université de Montréal Département de Mathématiques, February 2006
Mixing Time Bounds Via the Spectral Profile
Seymour Sherman Lecture and Conference, Indiana University, April 2006
Probability Seminar, UC-Berkeley Department of Mathematics, April 2006
Probability Seminar, Stanford University Department of Mathematics, October 2005
Probability Seminar, UC-San Diego Department of Mathematics, October 2005
Mixing Times for Top to Bottom Shuffles
Combinatorics Seminar, MIT Department of Mathematics, February 2005
Probability Seminar, Cornell University Department of Mathematics, February 2005
Workshop on Markov Chains, MSRI, January 2005
Probability Seminar, UW-Madison Department of Mathematics, January 2005
Estimating Convergence Rates for Finite Markov Chains
Probability Seminar, Univ of Toronto Dept. of Mathematics, December 2004
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