Regular biography
Elchanan Mossel is a professor of mathematics at the Massachusetts Institute of Technology, affiliated with the Mathematics Department and the Statistics and Data Science Center of the MIT Institute for Data, Systems and Society. His research spans probability, combinatorics, and inference, with interests in combinatorial statistics, discrete Fourier analysis, randomized algorithms, computational complexity, Markov random fields, social choice, game theory, evolution, and the mathematical foundations of deep learning. His work includes contributions to discrete function inequalities, isoperimetry, and hypercontractivity, leading to the proof that Majority is Stablest and confirming the optimality of the Goemans-Williamson MAX-CUT algorithm. Mossel has also made advances in phylogenetic reconstruction, Gibbs samplers, and inference problems for block models and planted partitions. He joined MIT as a full professor in 2016.
Scholar-generated biography
Elchanan Mossel is a Professor of Mathematics at MIT, specializing in Combinatorial Statistics, Discrete Fourier Analysis and Influences, and Randomized Algorithms. His research explores the theoretical foundations of probabilistic methods in combinatorics and computer science, with a focus on understanding the behavior of complex systems under uncertainty. Mossel's work includes contributions to the analysis of social networks, clustering algorithms, and the design of efficient algorithms for optimization problems. His publications address topics such as the inapproximability of constraint satisfaction problems, the reconstruction of Markov random fields, and the analysis of noisy sorting algorithms. His research has significant implications for both theoretical computer science and statistical physics.