Venkatesan Guruswami, or Venkat, as his friends and colleagues call him, received his Bachelor's degree from the Indian Institute of Technology at Madras in 1997. He is grateful to his undergraduate research advisor, C. Pandu Rangan, for initiating him to the joys of theoretical computer science. Venkat received his Ph.D. from the Massachusetts Institute of Technology in 2001 under the excellent advisorship of Madhu Sudan.

Venkat is currently an Associate Professor in the Computer Science Department at Carnegie Mellon University. Earlier, during 2002-09, he was a faculty member at the University of Washington. Venkat was a Miller Research Fellow at UC Berkeley during 2001-02, and was a member of the School of Mathematics, Institute for Advanced Study during 2007-08.

Venkat's research interests span several topics including the theory of error-correcting codes, approximability of fundamental optimization problems, pseudorandomness, probabilistically checkable proofs, computational complexity theory, and algebraic algorithms.

Venkat currently serves on the editorial boards of the SIAM Journal on Computing, the IEEE Transactions on Information Theory, and the ACM Transactions on Computation Theory, and is program committee chair for the 2012 Computational Complexity conference. Venkat is a recipient of the Presburger award, the Packard Fellowship, the Sloan Fellowship, the NSF CAREER award, the ACM Doctoral Dissertation Award, and the IEEE Information Theory Society Paper Award.

In his (sadly limited) spare time, Venkat enjoys traveling, ethnic vegetarian food, racquet sports, hiking/running within his humble limits, and listening to Carnatic music.

Yuan Zhou is a Ph.D. student in the Computer Science Department at Carnegie Mellon University. His advisors are Ryan O'Donnell and Venkatesan Guruswami. Yuan was an undergraduate student in the Microsoft Special Pilot CS Class supervised by Prof. Andrew Yao at Tsinghua University, and received his Bachelor's degree in 2009. His main research interests are in approximation algorithms, hardness of approximation, and analysis of Boolean functions. He is also interested in algorithmic mechanism design, algebraic dichotomy theory, coding theory, and their relations to the theory of approximation algorithms.