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Martin J. Wainwright

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Biography Publications Research Teaching Prospective Students Group members Directions to Campus  

Department of Electrical Engineering and Computer Sciences
Department of Statistics
University of California at Berkeley

Contact information

EECS information:

263 Cory Hall
Berkeley, CA 94720
Phone: (510) 643-1978
Fax: (510) 643-7846
Email: x@y with x=wainwrig
Statistics information:

421 Evans Hall #3860
Berkeley, CA 94720-3860
Phone: (510)-643-1975
Fax: (510) 642-7892
Email: x@y with x=wainwrig

Research affiliations and useful links

  • Designated Emphasis in Communication, Computation and Statistics: An interdisciplinary program that bridges the Department of Statistics and the Department of Electrical Engineering and Computer Sciences.

  • Statistical Machine Learning: A group of researchers and students from EECS and Statistics.

    Wireless Foundations: A communications and signal processing group which is housed in the Wong Center in the EECS Department.

    Some seminars and reading groups

    Upcoming seminars in the Department of Statistics.
    Signal Processing, Networking and Communication Seminar in the Department of EECS.

    Research areas

  • High-dimensional statistics
  • Graphical models and machine learning
  • Statistics and privacy
  • Non-parametric statistics
  • Distributed algorithms and optimization


    Graphical models and message-passing
    High-dimensional statistics
    Statistics and privacy
    Non-parametric statistics
    Optimization and distributed algorithms
    Coding, data compression, algorithms
    Statistical image processing
    Statistical approaches to biological vision

    Tutorial materials

  • Tutorial Materials on High-Dimensional Statistics:
  • Slides from lectures (PDF)
  • Statistical Science Paper (PDF)

  • Tutorial Materials on Graphical Models, Variational Methods and Message-Passing
    Machine Learning Summer School, Kyoto, Japan. September 2012
  • Slides (Part I) Basics, max-product and LP relaxation
  • Slides (Part II) Sum-product, variational formulation
  • Slides (Part III) Learning graphical models from data
  • Rough lecture notes: On factorization, Markov properties, Hammersley-Clifford, message-passing algorithms, junction tree, and basic aspects of graphical model estimation.
  • Wainwright and Jordan monograph: More advanced material on exponential families, duality, and variational methods.

  • Tutorial Lectures on Linear Programming Decoding and Conic Relaxations: Slides (PDF)

  • Current group members

    Graduate students

  • Mert Pilanci
  • Nihar Shah
  • Yuting Wei
  • Fanny Yang (mail ATSYMBOL
  • Yuchen Zhang

    Postdoctoral researchers

  • Sivaraman Balakrishnan
  • Yudong Chen
  • Mahdi Soltanolkotabi
  • Yun Yang


  • Alekh Agarwal Research Scientist, Microsoft Research, New York.
  • Arash Amini Assistant Professor, Dept. of Statistics, UCLA
  • Joseph Bradley Databricks
  • Alexandros D.G. Dimakis Associate Professor, Department of ECE, UT Austin
  • John Duchi, Assistant Professor, Departments of Statistics and EE, Stanford University
  • Pamela Lee, Associate, Gibson, Dunn & Crutcher
  • Po-Ling Loh, Assistant Professor, Department of Statistics, Univ. Pennsylvania
  • Matt Johnson, Postdoc, Harvard University
  • Sahand Negahban Assistant Professor, Department of Statistics, Yale University.
  • XuanLong Nguyen Associate Professor, Department of Statistics, Univ. Michigan
  • Nima Noorshams, Qualcomm Research
  • Garvesh Raskutti Assistant Professor, Department of Statistics, Univ. Wisconsin-Madison
  • Pradeep Ravikumar Assistant Professor, Department of CS, UT Austin
  • Prasad Santhanam Assistant Professor, Department of ECE, University of Hawaii
  • Sameer Vermani, Engineer, Qualcomm
    Last updated 09/2014