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ehsan [at] eecs [dot] berkeley [dot] edu

University of California, Berkeley
TRUST Center
Room 337 Cory Hall
Engineering Department
Berkeley, Ca 94720-1774


Ehsan Elhamifar

Postdoctoral Fellow
Electrical Engineering and Computer Science Department
University of California, Berkeley

About me

  • I am a postdoctoral fellow in the Electrical Engineering and Computer Science (EECS) department at the University of California, Berkeley, working with Prof. Shankar Sastry. I obtained my PhD in Fall 2012 from the Electrical and Computer Engineering (ECE) department at Johns Hopkins University, under the guidance of Prof. Rene Vidal.

  • News: During January to April 2015, I gave invited talks on my research at several institutions including CMU, UIUC, USC, Northeastern, Penn State, Ohio State, Boston University, NYU and UC Berkeley.

  • News: I am co-organizing the tutorial on "Sparse and Low-Rank Modeling for High-Dimensional Data Analysis" in CVPR 2015 in Boston, MA.


  • Ph.D., Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD
  • M.S.E., Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD
  • M.S., Electrical Engineering, Sharif University of Technology, Tehran, Iran
  • B.S., Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran


    My research addresses challenges related to analysis of large amounts of high-dimensional data with nuisances. I develop provably correct and efficient methods to uncover low-dimensional structures in data and use them to solve a variety of real-world problems in computer vision, robotics, energy systems and more. The areas in which I work are:

  • Data Analysis and Machine Learning: Multi-Manifold Data Analysis, Clustering and Classification, Dimensionality Reduction, Learning Dynamical Systems, Active Learning
  • Signal/Information Processing and Optimization: Sparse and Low-Rank Recovery, Compressive Sensing, Energy Disaggregation, Distributed Optimization
  • Computer Vision and Robotics: Motion/Video Segmentation, Face/Activity Recognition, Calibration and 3D Reconstruction in Camera Networks, Multiple View Geometry, Adaptive Inverse Modeling

  • Sparse Subspace Clustering
  • Subset Selection and Dataset Summarization
  • Provable Decision Making for Human-in-the-Loop Systems
  • Energy Disaggregation by Learning 'Powerlets'

Recent Publications

Complete List of Publications


Invited Talks

  • "Provable Learning Algorithms via Sparse Modeling," Google, Mountain View, 2014.
  • "Sparse Modeling for High-Dimensional Multi-Manifold Data Analysis," Stanford, UCLA, USC, JHU, UWashington, 2014.
  • "Learning All by Selecting a Few," Sparse Modeling Mini-Symposium at SIAM Annual Meeting, 2012.
  • "Learning All by Selecting a Few," EECS Department, University of California at Berkeley, 2012.
  • "Sparsity in Unions of Subspaces for Classification and Clustering of High-Dimensional Data," Allerton Conference on Communication, Control, and Computing, 2011.

Awards and Honors

  • Ranked 2nd among graduate students in Electrical Engineering, Control Division, Sharif University of Technology, Iran.
  • Ranked 33rd in the nation-wide university entrance examination on Electrical Engineering among 11,500 university students.
  • Ranked 1st among undergraduate students in Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran.
  • Honored for dual-degree studies in Biomedical and Electrical Engineering, Amirkabir University of Technology, Tehran, Iran.
  • Ranked 1st among 138 graduates from Malek Ashtar High School, Mashhad, Iran.
  • Honored as one of "The Best Hundred Young Mathematicians in Iran" in National Mathematics Olympiad, Iran.
  • Honored as one of "The Best Hundred Young Computer Scientists in Iran" in National Computer Science Olympiad, Iran.

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