Hi! I am an assistant professor in the
Decision, Risk, and Operations division at
Columbia Business School.
Prior to July 2019, I was a postdoctoral researcher at Google Research.
In July 2018, I received my Ph.D. from the MIT Operations Research Center.
I spent 2013-2015 as a co-founder of Lunarch Studios, the start-up that designed the strategy game Prismata. During those years, I had also been a research intern at Google, and a trading intern at Jane Street Capital.
I completed my undergraduate degree in 2010 from the University of Waterloo, majoring in Pure Mathematics and Combinatorics/Optimization. During that time, I competed in many international poker tournaments. In 2011 I founded the annual poker class at MIT, which can be accessed on MIT OpenCourseWare.
Research
Broadly speaking, I am interested in designing data-driven algorithms and analyzing their performance, usually in online decision-making settings.
Specific topics from my recent focus include prophet inequalities and viewing assortment optimization through the lens of mechanism design.
My research is motivated by applications in revenue management, such as product recommendation, online and sequential assortment optimization, and selling reusable resources. I am also interested in supply chain management, especially pertaining to e-commerce fulfillment and rationing during shortages.
Below is a list of my available papers, sorted by topic.
Please see my CV for a list of papers sorted by publication status.
Assortment Optimization and Mechanism Design
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When is Assortment Optimization Optimal?
Management Science, 2022 (Articles in Advance)
*One-page abstract forthcoming in the Proceedings of the 23rd ACM conference on Economics and Computation (EC), 2022
*2nd Place, Rothkopf Junior Researcher Paper Prize for Auctions and Market Design, 2021
*Selected for spotlight presentation in the INFORMS Revenue Management and Pricing Conference, 2022
*Selected for presentation in the INFORMS Market Design Workshop at EC, 2021
*Selected for presentation in the MSOM Service SIG, 2021
*Selected for oral presentation in the Market Innovation Workshop, 2021
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Revenue-Optimal Deterministic Auctions for Multiple Buyers with Ordinal Preferences over Fixed-Price Items
ACM Transactions on Economics and Computation (TEAC), Forthcoming
*Invited submission from the Proceedings of the 16th Conference on Web and Internet Economics (WINE), 2020
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Separation between Second Price Auctions with Personalized Reserves and the Revenue Optimal Auction with Balasubramanian Sivan
Operations Research Letters, 2020
Prophet Inequalities
Online and Stochastic Matching
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Follow Your Star: New Frameworks for Online Stochastic Matching with Known and Unknown Patience
with Brian Brubach, Nathaniel Grammel, Aravind Srinivasan
Operations Research, Major Revision
*Preliminary version appeared in the Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
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Algorithms for Online Matching, Assortment, and Pricing with Tight Weight-dependent Competitive Ratios with David Simchi-Levi
Operations Research, 2020
*One-page abstract, Tight Weight-dependent Competitive Ratios for Online Edge-weighted Bipartite Matching and Beyond, appeared in the Proceedings of the 20th ACM conference on Economics and Computation (EC), 2019
*Finalist, George E. Nicholson Student Paper Competition, 2017
Online and Stochastic Knapsack
Bundling
Other Revenue Management
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Bifurcating Constraints to Improve Approximation Ratios for Network Revenue Management with Reusable Resources with Jackie Baek
Operations Research, 2022 (Articles in Advance)
*One-page abstract, Prophet Inequalities on the Intersection of a Matroid and a Graph, appeared in the Proceedings of the 12th International Symposium on Algorithmic Game Theory (SAGT), 2019
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Inventory Balancing with Online Learning with Wang Chi Cheung, David Simchi-Levi, Xinshang Wang
Management Science, 2022
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Dynamic Pricing (and Assortment) under a Static Calendar with David Simchi-Levi, Jinglong Zhao
Management Science, 2021
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On Policies for Single-leg Revenue Management with Limited Demand Information with David Simchi-Levi, Chung-Piaw Teo
Operations Research, 2021
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Assortment Planning for Recommendations at Checkout under Inventory Constraints with Xi Chen, David Simchi-Levi, Linwei Xin
Mathematics of Operations Research, under 3rd Round Review
*Covered in Chicago Booth Review, 2018
*1st Place, Chinese Scholars Association for Management Science and Engineering (CSAMSE) Best Paper Award
sponsored by Columbia Business School, 2017
*2nd Place, POMS Hong Kong Student Paper Competition, 2017
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Multi-Stage and Multi-Customer Assortment Optimization With Inventory Constraints
with Elaheh Fata, David Simchi-Levi
Operations Research, Major Revision
Optimization Theory
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Distributionally Robust Linear and Discrete Optimization with Marginals with Louis Chen, Karthik Natarajan, David Simchi-Levi, Zhenzhen Yan
Operations Research, 2022 (Articles in Advance)
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The Convex Relaxation Barrier, Revisited: Tightened Single-Neuron Relaxations for Neural Network Verification with Christian Tjandraatmadja, Ross Anderson, Joey Huchette, Krunal Patel, Juan Pablo Vielma
Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS), 2020
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Strong Mixed-Integer Programming Formulations for Trained Neural Networks with Ross Anderson, Joey Huchette, Christian Tjandraatmadja, Juan Pablo Vielma
Math Programming, 2020
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Distributionally Robust Max Flows with Louis Chen, Jim Orlin, David Simchi-Levi
Proceedings of the 3rd ACM-SIAM Symposium on Simplicity in Algorithms (SOSA), 2020
Fairness in Online Matching
Video Games
Other
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