About the Author(s)
Joshua Buresh-Oppenheim Postdoctoral Fellow Simon Fraser University jburesho[ta]cs[td]sfu[td]ca http://www.cse.ucsd.edu/users/jboppenheim
Josh Buresh-Oppenheim received his Ph. D. from the University of Toronto under the supervision of Toni Pitassi in 2005. Since then, he has been a postdoc at the University of California, San Diego, hosted by Russell Impagliazzo, and at Simon Fraser University, hosted by David Mitchell. His research interests include propositional proof complexity, classifying algorithmic techniques, and computational complexity in general. In his spare time, Josh is heir-apparent to the principality of Liechtenstein. When not on missions of diplomacy, he enjoys reënacting episodes of Welcome Back, Kotter, critiquing trade shows for the New Orleans Times Picayune, and fabricating biographies.
Nicola Galesi Associate Professor Università degli Studi di Roma La Sapienza galesi[ta]di[td]uniroma1[td]it http://www.dsi.uniroma1.it/~galesi/
Nicola Galesi received his Ph. D. in Computer Science from the Universitat Politecnica de Catalunya of Barcelona (Spain) in 2000 under the direction of Maria Luisa Bonet. At present, he is an associate professor in the Department of Computer Science at Università degli Studi di Roma "La Sapienza" (Italy). Formerly (01/05) he held a similar position in the Department of Computer Science of the Universitat Politecnica de Catalunya. He was a postdoc at the Institute for Advanced Study as a member of the School of Mathematics during the Special Year in Computational Complexity (00/01) and in 2002 he was a postdoc in the Department of Computer Science of the University of Toronto (Toronto, Canada) in the Theory Group. His main research interest is in complexity theory, especially in lower bounds in proof complexity. In addition to spending time with his family, Nicola practices Taoist Tai Chi, is an avid reader and moviegoer, likes to play the guitar, and enjoys Japanese cuisine.
Shlomo Hoory Postdoctoral Fellow University of British Columbia shlomoh[ta]cs[td]ubc[td]ca http://www.cs.ubc.ca/~shlomoh
Shlomo Hoory received his Ph. D. in Computer Science from the Hebrew University Jerusalem in 2002 under the supervision of Nati Linial. Since then he has been a postodoctoral fellow at the theory group at the University of Toronto and the University of British Columbia. In April 2006 he will join IBM Haifa Research Lab. His research interests include algebraic graph theory, expanders, graphs of high girth, cryptography, and error correcting codes. He is especially interested in extremal properties of irregular graphs. Apart from academic life, he has practical experience from his long episodes in the high-tech industry. This experience includes programming, real time systems, OS internals, VLSI design, and digital signal processing.
Avner Magen Assistant Professor University of Toronto avner[ta]cs[td]toronto[td]edu http://www.cs.toronto.edu/~avner
Avner Magen did his B. Sc., M. Sc., and Ph. D. at the Hebrew University Jerusalem under the supervision of Nati Linial. He is now an assistant professor at the Department of Computer Science, University of Toronto. His main interest areas are metric embeddings, lower bounds to combinatorial optimization problems and approximation algorithms. He enjoys travelling and hiking.
Toniann Pitassi Professor University of Toronto toni[ta]cs[td]toronto[td]edu http://www.cs.toronto.edu/~toni
Toni Pitassi received bachelors and masters degrees from Pennsylvania State University and then received a Ph. D. from the University of Toronto in 1992 under the supervision of Stephen Cook. After that, she spent 2 years as a postdoc at UCSD, and then 2 years as an assistant professor (in mathematics with a joint appointment in computer science) at the University of Pittsburgh. For the next four years, she was a faculty member of the Computer Science Department at the University of Arizona. In the fall of 2001, she moved back to Toronto, where she is currently a professor in the Computer Science Department. Her research interests include proof complexity, circuit complexity, classifying algorithmic techniques, analysis of SAT-solvers, and the theory of machine learning.