Darshan Thaker

Darshan Thaker

Computer Science Ph.D. student

Johns Hopkins University


I am a Ph.D. student at Johns Hopkins University, where I am fortunate to be advised by Prof. René Vidal. My research interests broadly lie in theoretical machine learning and the foundations of data science in order to obtain provable guarantees for ML algorithms. One particular area of interest is the theory of deep learning, both from an optimization and generalization perspective.

I previously completed my MS in Computer Science at Columbia University, where I was advised by Prof. John Wright, and my BS degree in CS and Math at UT Austin.


  • Theoretical Machine Learning
  • Theory of Deep Learning
  • Non-Convex Optimization
  • Learning Theory


  • Ph.D. in Computer Science

    Johns Hopkins University

  • MS in Computer Science, 2019

    Columbia University

  • BS in Computer Science (Turing Scholars Honors), 2018

    The University of Texas at Austin

  • BS in Pure Mathematics, 2018

    The University of Texas at Austin

Industry Experience


Research Intern

Salesforce Research

Feb 2020 – May 2020 Palo Alto, California

Research Intern

The Curious AI Company

May 2018 – Aug 2018 Helsinki, Finland

Software Engineering Intern


May 2017 – Aug 2017 Menlo Park, California

Software Engineering Intern


May 2016 – Aug 2016 Mountain View, California

Machine Learning Intern


May 2015 – Aug 2015 Mountain View, California