I am an incoming first-year Ph.D. student in Management Science and Operations Management at the University of Chicago Booth School of Business, in the Stevens Doctoral Program. Before Booth, I studied at Stanford University, where I completed a BS in Mathematics and an MS in Computer Science.

I work in theoretical computer science, at the intersection of algorithms, combinatorics, and optimization. Broadly, I am interested in applying discrete mathematics, probability, and complexity theory to problems in this space. My more specific interests are in approximation algorithms and hardness of approximation for stochastic matching and welfare maximization problems, together with their applications to resource allocation in online platforms and markets.

Most recently, my undergraduate honors thesis with Jan Vondrák introduced stochastic matching with batch allocations, a variant of online stochastic matching in which agents receive batches of items. I proved hardness-of-approximation results via new reductions, and gave randomized approximation algorithms that beat the classical $1 - 1/e$ ratio by combining a global maximum matching with an LP relaxation.

Research interests

• Approximation algorithms and hardness of approximation
• Matching theory, stochastic and online matching
• Submodular optimization and welfare maximization
• Algorithmic game theory and resource allocation in markets
• Combinatorics and enumeration (meanders, self-avoiding walks, heapable permutations)

Contact

The best way to reach me is by email at mcho2@chicagobooth.edu.