Mahdi Soltanolkotabi

    I am an assistant professor in the Ming Hsieh Department of Electrical Engineering at the University of Southern California.
    My research focuses on design and mathematical understanding of computationally efficient algorithms for optimization, high dimensional statistics, machine learning, signal processing and computational imaging. Lately, I've been developing and analyzing algorithms for non-convex optimization with provable guarantees of convergence to the global optimum. A particular focus on the application side has been on computational imaging.
    Prior to joining USC I spent a year as a postdoc in the AMPLAB at UC Berkeley sponsored by Ben Recht and Martin Wainwright. I obtained my Ph.D. in Electrical Engineering from Stanford in 2014 advised by Emmanuel Candes.


    • Robust Subspace Clustering.
      - Stanford Biostatistics Seminar, February 2014.
      - ICML Spectral Learning Workshop, June 2013.
      - Asilomar Conference on Signals, Systems, and Computers.
      - MURI annual meeting, Princeton, October 2012.
      - Information Theory and Applications workshop, Feb. 2013.
    • A Geometric Analysis of Subspace Clustering with Outliers.
      - Berkeley Robotics Lab, Febuary 2012.
      - High-Dimensional Phenomena in Statistics and Machine Learning Seminar, Georgia Tech., July 2012.
      - Workshop on Modern Massive Data Sets (MMDS), Stanford, July 2012.


    EE 364a: Convex Optimization, Summer 2011.


    Stanford CS:
    - CS 229: Machine Learning, Fall 2012.
    Stanford EE:
    - EE 278: Statistical Signal Processing, Summer 2010.
    Stanford Math:
    - Math 104: Linear Algebra, Winter 2012.
    Stanford Statistics: