Elchanan Mossel

Elchanan Mossel is an Israeli-American mathematician and theoretical computer scientist noted for contributions to probability theory, analysis of boolean functions, percolation, and social choice theory. His work connects ideas from Paul Erdős-inspired combinatorics, Andrey Kolmogorov-style probability, and algorithmic aspects of Alan Turing-era computation, influencing research across statistical physics and machine learning communities. Mossel has held faculty positions at leading institutions and frequently collaborates with researchers at institutes such as the Institute for Advanced Study, Princeton University, and Microsoft Research.

Early life and education

Mossel was born in Israel and completed undergraduate and graduate study at the Hebrew University of Jerusalem and the Weizmann Institute of Science, studying under advisors linked to traditions of Paul Erdős and Erdős–Rényi model-era graph theory. He pursued doctoral and postdoctoral work that interfaced with researchers from University of Cambridge, Harvard University, and Massachusetts Institute of Technology, situating him among contemporaries influenced by figures like Oded Schramm, Michel Talagrand, and Persi Diaconis. During his formative years he engaged with seminars at the Jerusalem School of Mathematics and workshops at institutions including the Simons Institute for the Theory of Computing and the Mathematical Sciences Research Institute.

Research and contributions

Mossel's research spans rigorous results in percolation theory, noise stability, and influences in discrete functions, building on frameworks developed by Kenneth Arrow in social choice and by Robert B. Griffiths in statistical mechanics. He proved structural theorems related to the Majority is Stablest theorem, connecting to conjectures by scholars such as Subhash Khot and techniques from the Unique Games Conjecture literature. His work on influences of variables and invariance principles synthesizes methods from Miklós Rényi-style probabilistic combinatorics, Erdős–Rényi model insights, and analytic approaches reminiscent of Jean Bourgain and Terence Tao. Mossel has contributed to understanding noise sensitivity in models related to percolation and to algorithmic hardness results relevant to the Probabilistically Checkable Proofs framework and the Szemerédi regularity lemma-inspired graph limits. Collaborations with researchers such as Ryan O'Donnell, Eliezer Yudkowsky, and Yuval Peres (among many) produced influential papers on the interplay between boolean function analysis, learning theory, and stochastic processes like Brownian motion and branching processes linked to Galton–Watson process models.

Academic career and positions

Mossel has been a faculty member at the Massachusetts Institute of Technology and later at the University of California, Berkeley, and held positions and visiting appointments at the Weizmann Institute of Science, the Hebrew University of Jerusalem, and research programs at the Institute for Advanced Study. He has served as a mentor in programs affiliated with the Simons Foundation and given invited lectures at conferences organized by the American Mathematical Society, the Association for Computing Machinery, and the International Congress of Mathematicians. Mossel has supervised doctoral students who went on to positions at places such as Google Research, Microsoft Research, Columbia University, and Stanford University, and he has participated in editorial roles for journals connected to the American Mathematical Society and publishing venues of the Association for Computing Machinery.

Awards and honors

Mossel's work has been recognized by invitations to speak at major venues such as the International Congress of Mathematicians and by awards and fellowships from organizations including the Simons Foundation and national research councils in Israel and the United States. His papers have received prizes in theoretical computer science circles and he has been awarded grants from entities like the National Science Foundation and European funding bodies supporting research in probability and computation. He has been elected to program committees for conferences such as the Symposium on Theory of Computing and the Conference on Learning Theory.

Selected publications

- Mossel, E.; O'Donnell, R.; Oleszkiewicz, K. "Noise stability of functions with low influences and applications to hardness of approximation." Publications and proceedings connected to the Association for Computing Machinery and IEEE conferences. - Mossel, E.; Neeman, J. "Robust optimality of the Gaussian noise stability and applications to isoperimetry." Works linked to developments by Borell and Ehrhard. - Mossel, E.; Peres, Y. "Reconstruction on trees and the Ising model." Papers engaging with themes by Hendrik Kesten and Harry Kesten. - Mossel, E.; O'Donnell, R.; Servedio, R. A. "Learning theory and boolean function analysis." Contributions cited alongside research by Leslie Valiant and Valiant's framework. - Mossel, E. "Sharp thresholds and graph properties." Research situated among studies by Paul Erdős and Alfréd Rényi.

Category:Living people