I have the pleasure of working with some fantastic students at Columbia. If you are interested in becoming a student, please apply here.Harsh Sheth (co-advised with Vineet Goyal)
Ryan McNellis, 2019, Applied Research Scientist at Amazon
Yunjie Sun, 2019, Sr. Revenue Management Analyst & Data Scientist at TripAdvisor
Michael Hamilton, 2019, Assistant Professor at Katz Graduate School of Business, University of Pittsburgh
The Value of Flexibility from Opaque Selling, with D. D. Yao and Y. Zhou
Pricing with Fairness, with M. C. Cohen and X. Lei
Loot Box Pricing and Design, with N. Chen, M. L. Hamilton, and X. Lei
Major revision in Management Science.
• Invited to present at the Federal Trade Commission (FTC) Workshop on Consumer Issues Related to Loot Boxes, 2019 (one of four research papers selected).
• 1st place for Xiao Lei, IBM Best Student Paper Award in Service Science, 2019.
Static Pricing: Universal Guarantees for Reusable Resources, with O. Besbes and Y. Sun
Major revision in Operations Research.
• Accepted in The 20th ACM Conference on Economics and Computation (EC), 2019.
• Spotlight presentation at INFORMS Revenue Management and Pricing (RMP), 2019 (top 20% of full paper submissions).
• Finalist (part 1 of 2), INFORMS Revenue Management and Pricing (RMP) Practice Award, 2019.
The Value of Personalized Pricing, with V. Gupta and M. L. Hamilton [code]
• Finalist, INFORMS Service Science Cluster Best Paper Award, 2018.
• Accepted in The 15th Conference on Web and Internet Economics (WINE), 2019.
Smart "Predict, then Optimize", with P. Grigas
Minor revision in Management Science.
The Power of Opaque Products in Pricing, with M. L. Hamilton
Major revision in Management Science.
• Accepted in The 13th Conference on Web and Internet Economics (WINE), 2017.
Retailing with Opaque Products, with Y. Wei
Major revision in Manufacturing & Service Operations Management.
Pricing Analytics for Rotable Spare Parts, with O. Besbes and Y. Sun
INFORMS Journal on Applied Analytics, forthcoming.
• Finalist, Daniel H. Wagner Prize for Excellence in Operations Research Practice, 2019.
• Finalist (part 2 of 2), INFORMS Revenue Management and Pricing (RMP) Practice Award, 2019.
Generalization Bounds in the Predict-then-Optimize Framework, with O. El Balghiti, P. Grigas, and A. Tewari
Advances in Neural Information Processing Systems 32 (NeurIPS), 2019.
A Practical Method for Solving Contextual Bandit Problems Using Decision Trees, with R. McNellis, S. Oh, and M. Petrik
Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence (UAI), 2017.
• Invited for oral presentation (top 10% of submissions).
Supply Chain Management with Online Customer Selection, with R. Levi
Operations Research, Vol. 64(2), p. 458-473, 2016.
The Submodular Joint Replenishment Problem, with M. Cheung, R. Levi, and D. B. Shmoys
Mathematical Programming, Vol. 158(1), p. 207-233, 2016.
From Cost Sharing Mechanisms to Online Selection Problems, with R. Levi
Mathematics of Operations Research, Vol. 40(3), p. 542-557, 2015.
Maximizing the Spread of Cascades Using Network Design, with D. Sheldon, B. Dilkina, R. Finseth, A. Sabharwal, J. Conrad, C. Gomes, D. Shmoys, W. Allen, O. Amundsen, W. Vaughan
Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence (UAI), p. 517-526, 2010.
• Invited for oral presentation (top 12% of submissions).
From Random Polygon to Ellipse: An Eigenanalysis, with C. F. Van Loan
SIAM Review, Vol. 52(1), p. 151-170, 2010. [demo by Jason Davies]
• Charles F. Van Loan selected this work as the subject for his 2018 John von Neumann Lecture.
Revenue management using dynamic customer selection, with R. Lederman. US Patent 2017/0358001.
Training a machine to dynamically determine and communicate customized, product-dependent promotions with no or limited historical data over a network>, with M. R. Ettl, S. Oh, M. Petrik, and R. K. Ravi. US Patent 2017/0046732.
Determining feature importance and target population in the context of promotion recommendation, with M. R. Ettl, S. Oh, M. Petrik, and R. K. Ravi. US Patent 2017/0046736.
IEOR 4418, Transportation Analytics and Logistics (B.S./M.S.), Fall 2016, Spring 2018, 2019, 2020
IEOR 4574, Business Analytics (B.S./M.S.), Spring 2016, 2017 (x2), 2018 (x2), 2019 (x2), 2020
IEOR 8100, Supply Chain Management: Classics and Recent Trends (Ph.D.), Spring 2016
IEOR 8100, Contextual Optimization for Prescriptive Analytics (Ph.D.), Fall 2019