Mahdi Soltanolkotabi

Director USC Center on AI Foundations for Science (AIF4S)
David and Lucile Packard Fellow
Andrew and Erna Viterbi Early Career Chair
Associate Professor, Departments of Electrical and Computer Engineering, Computer Science, and Industrial and Systems Engineering
University of Southern California

    Office: EEB 430
    Tel: 213-740-4456

    I am an associate professor in the Ming Hsieh Department of Electrical and Computer Engineering, Computer Science, and Industrial and Systems Engeineering (ISE) at the University of Southern California where I hold an Andrew and Erna Viterbi Early Career Chair. I am also the inaugural director of the USC Center on AI Foundations for Science (AIF4S). Prior to joining USC I spent a year as a postdoc in the AMPLAB at UC Berkeley mentored by Ben Recht and Martin Wainwright. I obtained my Ph.D. in Electrical Engineering from Stanford in 2014 advised by Emmanuel Candes.

    My research focuses on developing the mathematical foundations of learning from signals and data spanning optimization, artificial intelligence, machine learning, signal processing, high dimensional probability/statistics, and computational imaging. Over the last few years, I've been developing and analyzing algorithms for non-convex optimization with provable guarantees of convergence to generalizable global optima including those arising in deep learning. A particular focus on the application side has been on developing reliable AI for scientific and medical imaging applications.

    On the weekends you're most likely to find me cycling on the Pacific coast ranging from Malibu/Santa Monica mountains to Palos Verdes.


    • 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:
      I am currently collaborating with Nava College Prepatory Academy a school in Compton to help improve K-12 math/STEM education. I will be posting more details about these activities including curriculum development, lecture notes, excersize/puzzles, data modules etc. on this website (please check back for updates).
      I have also partnered with VAST: Viterbi Adopt-a-School Adopt-a-Teacher (VAST) and STEM educational outreach programs at USC Viterbi School of Engineering to engage in various educational outreach activities in local middle/high schools close to USC e.g. see VAST's reporting on one such activity here and stay tunned for more updates.