Hi! I am an associate 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
My research focuses on the theory of Online Algorithms and its implications for models in Revenue Management.
I have also worked on single-shot Revenue Maximization problems related to mechanism design, and some Other areas.
Recently, I have been interested in designing algorithms from samples/predictions, motivated by the large-scale data available in e-commerce fulfillment applications.
Algorithms from Samples/Predictions
E-commerce Fulfillment
Online Algorithms
Keywords include: Prophet Inequalities,
Online Matching,
Stochastic Knapsack,
Multi-secretary Regret
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Tightness without Counterexamples: A New Approach and New Results for Prophet Inequalities with Jiashuo Jiang, Jiawei Zhang
*One-page abstract appeared in the Proceedings of the 24th ACM conference on Economics and Computation (EC), 2023
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Degeneracy is OK: Logarithmic Regret for Network Revenue Management with Indiscrete Distributions with Jiashuo Jiang, Jiawei Zhang
Operations Research, Major Revision
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A Nonparametric Framework for Online Stochastic Matching with Correlated
Arrivals with Ali Aouad
*One-page abstract appeared in the Proceedings of the 24th ACM conference on Economics and Computation (EC), 2023
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On (Random-order) Online Contention Resolution Schemes for the
Matching Polytope of (Bipartite) Graphs with Calum MacRury, Nathaniel Grammel
*Preliminary version appeared in the Proceedings of the 34th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), 2023
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Tight Guarantees for Multi-unit Prophet Inequalities and Online Stochastic Knapsack with Jiashuo Jiang, Jiawei Zhang
Operations Research, Major Revision
*Preliminary version appeared in the Proceedings of the 33rd Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), 2022
*Jiashuo Jiang was a Finalist in the George E. Nicholson Student Paper Competition, 2022
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Tight Guarantees for Static Threshold Policies in the Prophet Secretary Problem with Nick Arnosti
Operations Research, Articles in Advance
*One-page abstract appeared in the Proceedings of the 23rd ACM conference on Economics and Computation (EC), 2022
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Improved Guarantees for Offline Stochastic Matching via new Ordered Contention Resolution Schemes with Brian Brubach, Nathaniel Grammel, Aravind Srinivasan
*Preliminary version appeared in the Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS), 2021
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A Competitive Analysis of Online Knapsack Problems with Unit Density with David Simchi-Levi, Jinglong Zhao
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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
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Improvements and Generalizations of Stochastic Knapsack and Markovian Bandits Approximation Algorithms
Mathematics of Operations Research, 2018
*Preliminary version, Improvements and Generalizations of Stochastic Knapsack and Multi-armed
Bandit Approximation Algorithms, appeared in the Proceedings of the 25th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), 2014
*Honorable Mention, INFORMS Optimization Society Student Paper Competition, 2017
Revenue Management
Keywords include:
Dynamic Pricing/Assortment, Product Ranking, Recommendations, Reusable Resources, Single-leg Revenue Management, Multi-stage Assortment Optimization
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Dynamic Pricing for Reusable Resources: The Power of Two Prices with Santiago Balseiro, Wenxin Zhang
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Online Matching Frameworks under Stochastic Rewards, Product Ranking, and Unknown Patience
with Brian Brubach, Nathaniel Grammel, Aravind Srinivasan
Operations Research, Forthcoming
*Preliminary version, Follow Your Star: New Frameworks for Online Stochastic Matching with Known and Unknown Patience, appeared in the Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 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, Articles in Advance
*Covered in Chicago Booth Review, 2018
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Bifurcating Constraints to Improve Approximation Ratios for Network Revenue Management with Reusable Resources with Jackie Baek
Operations Research (Technical Note), 2022
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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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Multi-Stage and Multi-Customer Assortment Optimization With Inventory Constraints
with Elaheh Fata, David Simchi-Levi
Operations Research, Major Revision
Single-shot Revenue Maximization
Keywords include:
Assortment Optimization, Mechanism Design, Bundling
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Assortment and Inventory Planning under Stockout-Based Substitution: The Many-Products Regime
with Jingwei Zhang, Huseyin Topaloglu
Operations Research, Major Revision
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When is Assortment Optimization Optimal?
Management Science, 2023
*One-page abstract appeared 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 MSOM Service SIG, 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), 2022
*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
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Constructing Demand Curves from a Single Observation of Bundle Sales with David Simchi-Levi
Proceedings of the 18th Conference on Web and Internet Economics (WINE), 2022
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Reaping the Benefits of Bundling under High Production Costs with David Simchi-Levi
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Other
Models for Social Applications
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
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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
Video Games
Uncategorized
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