Princeton University

School of Engineering & Applied Science

Emmanuel Abbe

Associate Professor of Electrical Engineering

Associate Professor in Program in Applied and Computational Mathematics

Associated Faculty in Mathematics


Room: B322 Engineering Quadrangle, 212 Fine Hall
Phone: 609-258-4692
Email: eabbe@princeton.edu
Webpage: Abbe Lab:

Education

  • Ph.D., Massachusetts Institute of Technology, 2008
  • M.S., Mathematics, EPFL, 2003

Emmanuel Abbe received his Ph.D. degree from the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology in 2008, and his M.S. degree from the Department of Mathematics at the Ecole Polytechnique Fédérale de Lausanne in 2003. He joined Princeton University as an assistant professor in 2012 and became associate professor in 2016, jointly in the Program for Applied and Computational Mathematics and the Department of Electrical Engineering. He is also an associate faculty in the Department of Mathematics at Princeton University since 2016. He is the recipient of the Foundation Latsis International Prize, the Bell Labs Prize, the NSF CAREER Award, the Google Faculty Research Award, the Walter Curtis Johnson Prize for Teaching Excellence and the von Neumann Fellowship from the Institute for Advanced Study.

Honors and Awards

  • Bell Labs Prize
  • Walter Curtis Johnson Prize for Teaching Excellence
  • NSF CAREER Award
  • Google Faculty Research Award
  • von Neumann Fellowship
  • Foundation Latsis International Prize

Selected Publications

    • E. Abbe, J. Fan, K. Wang, Y. Zhong

    Entry-wise eigenvector analysis for low-rank random matrix perturbations. Annals of Statistics.

    • E. Abbe, L. Massoulié, A. Montanari, A. Sly, N. Srivastava

    Group synchronization on grids.

    Mathematical Statistics and Learning. 

    • E. Abbe, 

    Community detection and stochastic block models: recent developments. 

    Special Issue of the Journal on Machine Learning Research, 2017

    • E. Abbe, C. Sandon, 

    Proof of the achievability conjectures for the general stochastic block model. 

    Communications on Pure and Applied Mathematics, 2017

  1. E. Abbe, C. Sandon,

           Achieving the KS threshold in the stochastic block model with linearized acyclic belief propagation, To appear in Proc. of Annual Conference on Neural Information Processing Systems (NIPS), Barcelona, 2016. (Or

    • E. Abbe, N. Alon, A. Bandeira, C. Sandon, 

    Linear Boolean classification, coding and “the critical problem”, 

    IEEE Transactions on Information Theory, 62(4):1667-1673, 2016.

    • E. Abbe, A. Bandeira, G. Hall, 

    Exact recovery in the stochastic block model, 

    IEEE Transactions on Information Theory, 62(1):471-487, 2016.

    • E. Abbe, A. Montanari, 

    Conditional random fields, planted constraint satisfaction and entropy concentration, 

    Theory of Computing, 11(17):413-443, 2015.

    • E. Abbe, A. Shpilka, A. Wigderson, 

    Reed-Muller codes for random erasures and errors, 

    IEEE Transactions on Information Theory, 61(10):5229-5252, 2015.

    • E. Abbe, 

    Randomness and dependencies extraction via polarization, with applications to Slepian-Wolf coding and secrecy, 

    IEEE Transactions on Information Theory, 61(5):2388-2398, 2015.

    • E. Abbe, A. Montanari, 

    On the concentration of the number of solutions of random satisfiability formulas, 

    Random Structures and Algorithms, vol. 45, issue 3, pp. 362-382, 2014.