About Me

Hi! I am a postdoc in the theory group at the University of Toronto. Previously, I was a PhD student at the Department of Computer Science at UBC, where I was fortunate to be advised by Nick Harvey. I am broadly interested in randomized algorithms, machine learning theory, and mechanism design.

Selected Publications

• Optimal anytime regret with two experts, FOCS 2020
  (with Nick Harvey, Ed Perkins, Sikander Randhawa)
• The Vickrey Auction with a Single Duplicate Bidder Approximates the Optimal Revenue, EC 2019
  (with Hu Fu and Sikander Randhawa)
• Nearly-tight sample complexity bounds for learning mixtures of Gaussians via compression schemes, best paper at NeurIPS 2018
  (with Hassan Ashtiani, Shai Ben-David, Nick Harvey, Abbas Mehrabian, Yaniv Plan)
• Nearly-tight VC-dimension bounds for piecewise linear neural networks, COLT 2017
  (with Peter L. Bartlett, Nick Harvey, Abbas Mehrabian)
• A simple tool for bounding the deviation of random matrices on geometric sets, in Geometric Aspects of Functional Analysis
  (with Abbas Mehrabian, Yaniv Plan, and Roman Vershynin)