Bio
Professor Singal’s research focuses on analytics in a mix of marketplaces, including transportation, labor, sports, and advertising. He leverages data to develop application-driven models that help businesses evaluate current systems and optimize decision-making. Outside academia, Singal enjoys playing tennis and has played at a national level.
Current Research Topics
Marketplace analytics, data-driven modeling and optimization, attribution
Professional Activities
Academic positions
- Assistant Professor of Business Administration, Tuck School of Business, 2021–present
Nonacademic positions
- Data Scientist Intern (Supply Chain Optimization Technologies), Amazon, 2020–21
- Data Scientist Intern (Media and Advertising Solutions), Adobe, 2017
- Quantitative Research Co-op (Asset Mix and Risk), Ontario Teachers’ Pension Plan, 2013–14
Editorial positions (reviewer)
- Management Science
- Operations Research
- Manufacturing & Service Operations Management
- Production and Operations Management
- Transportation Science
Awards
- Harvey H. Bundy III T’68 Faculty Fellow, 2022
- 2nd place, Michael H. Rothkopf Junior Researcher Paper Prize (INFORMS Auctions and Market Design), 2022
- Finalist, Data-driven Research Challenge (INFORMS Revenue Management and Pricing), 2021
- 2nd place, Jeff McGill Student Paper Award (INFORMS Revenue Management and Pricing), 2019
- Cheung-Kong Graduate School of Business Fellowship, Columbia University, 2019, 2018
- Outstanding Teaching Assistant Award, Columbia University, 2018
- Highly Commended, The Undergraduate Awards, 2015
- University of Toronto Excellence Award, 2013
Working Papers
- With M. B. Haugh, “Bounding Counterfactuals in Hidden Markov Models and Beyond,” preliminary version appeared in ICML, 2023
- With O. Besbes, V. Goyal, and G. Iyengar, “Effective Wages under Workforce Scheduling with Heterogeneous Time Preferences”
- With G. Michailidis and H. Ng, “Flow-based Attribution in Graphical Models: A Recursive Shapley Approach,” preliminary version appeared in ICML, 2021
Selected Publications
- With O. Besbes, A. Desir, V. Goyal, and G. Iyengar, “Shapley Meets Uniform: An Axiomatic Framework for Attribution in Online Advertising,” Management Science, 68(10), 2022
- With M. B. Haugh, “How to Play Fantasy Sports Strategically (And Win),” Management Science, 67(1), 2021
- With J. Bhandari and D. Russo, “A Finite Time Analysis of Temporal Difference Learning with Linear Function Approximation,” Operations Research, 69(3), 2021
- With T. C. Y. Chan, “A Bayesian Regression Approach to Handicapping Tennis Players Based on a Rating System,” Journal of Quantitative Analysis in Sports, 14(3), 2018
- With T. C. Y. Chan, “A Markov Decision Process-based Handicap System for Tennis,” Journal of Quantitative Analysis in Sports, 12(4), 2016