Ph.D. (Berkeley)
Adjunct Assistant Professor

Computational Complexity, Optimization, Approximation Algorithms, Random Graphs, Learning and Testing
Research Areas
  • Artificial Intelligence
  • Computer Theory
    • Theory and Algorithms



Before joining The Chinese University of Hong Kong, I was a postdoc researcher at Microsoft Research New England. Before that, I got a PhD in theoretical computer science at UC Berkeley. My advisors were Luca Trevisan and Elchanan Mossel. Earlier, I did my masters at University of Toronto, under Michael Molloy, and my undergrad at The Chinese University of Hong Kong, working with Leizhen Cai. I am interested in understanding the limitations of approximation algorithms, especially convex optimization algorithms. I am also interested in random graphs, testing and learning.