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Allan Sly is the Anthony H. P. Lee '79 Professor of Mathematics at Princeton University. He specializes in discrete probability theory and its applications to statistical physics and theoretical computer science. Sly's research is focused on stochastic processes and networks, with significant contributions to the analysis of mixing for Markov chains, particularly in relation to Glauber dynamics and phase transitions in computational complexity. He has produced substantial work on topics such as the Ising model, random constraint satisfaction problems, and computational phase transitions, with influential papers in leading journals. Sly completed his PhD in Statistics at UC Berkeley in 2009 and later undertook postdoctoral research at Microsoft Research. His teaching includes advanced courses in percolation theory.
GRE scores are not accepted. Ph.D. is the primary degree; students are not required to hold an M.S.E. prior to admission.