Upcoming/Recent Talks

Bounding Counterfactual Outcomes of Health Insurance Delay-and-Deny Practices
  • MSOM Healthcare SIG (London): June 27
  • Questrom School of Business (Boston): Oct 16
  • INFORMS (Atlanta): Oct 26

Peer Review Market Design: Effort-Based Matching and Admission Control
  • ISB (Hyderabad): Feb 28
  • ACMS (Dartmouth): May 6
  • TRG (Dartmouth): June 3
  • RMP (NYC): July 16
  • INFORMS (Atlanta): Oct 26
  • UMD (Maryland): Nov 21

Education

Ph.D. in Operations Research
2015 - 2020
Columbia University
CKGSB Fellow

B.A.Sc. in Industrial Engineering
2010 - 2015
University of Toronto
Ranked 1 (out of 100 students)

Working Papers

Peer Review Market Design: Effort-Based Matching and Admission Control
Craig Fernandes, James Siderius, and Raghav Singal
[SSRN]

Online Allocation with Heterogeneous Supply and Minimum Workload Guarantees
Garud Iyengar and Raghav Singal
[SSRN] [Video]

Churning While Experimenting: On the Long-Term Optimality of Short-Term Churn Minimization
Michael Hamilton and Raghav Singal
[SSRN]

Journal Publications

Bounding Counterfactual Outcomes of Health Insurance Delay-and-Deny Practices
Martin Haugh and Raghav Singal
Manufacturing & Service Operations Management, forthcoming
[Journal] [SSRN] [Press]

A Counterfactual Analysis of the Dishonest Casino
Martin Haugh and Raghav Singal
Journal of Causal Inference, forthcoming
[arXiv] [Code]

Workforce Scheduling with Heterogeneous Time Preferences: Effective Wages and Workers' Supply
Omar Besbes, Vineet Goyal, Garud Iyengar, and Raghav Singal
Manufacturing & Service Operations Management, 2024
[Journal] [SSRN] [Video] [Press]

Axiomatic Effect Propagation in Structural Causal Models
Raghav Singal and George Michailidis
Journal of Machine Learning Research, 2024
[Journal]

Model-Free Approximate Bayesian Learning for Large-Scale Conversion Funnel Optimization
Garud Iyengar and Raghav Singal
Production and Operations Management, 2024
[Journal] [arXiv] [Code]

Shapley Meets Uniform: An Axiomatic Framework for Attribution in Online Advertising
Raghav Singal, Omar Besbes, Antoine Desir, Vineet Goyal, and Garud Iyengar
Management Science, 2022
[Journal] [SSRN] [Video] [Press]

How to Play Fantasy Sports Strategically (and Win)
Martin Haugh and Raghav Singal
Management Science, 2021
[Journal] [SSRN] [Video] [Press]

A Finite Time Analysis of Temporal Difference Learning with Linear Function Approximation
Jalaj Bhandari, Daniel Russo, and Raghav Singal
Operations Research, 2021
[Journal] [arXiv]

A Bayesian Regression Approach to Handicapping Tennis Players Based on a Rating System
Timothy C. Y. Chan and Raghav Singal
Journal of Quantitative Analysis in Sports, 2018
[Journal] [PDF] [TennisNeutral]

A Markov Decision Process-Based Handicap System for Tennis
Timothy C. Y. Chan and Raghav Singal
Journal of Quantitative Analysis in Sports, 2016
[Journal] [PDF]

Peer-Reviewed Conference Proceedings

Peer Review Market Design: Effort-Based Matching and Admission Control
Craig Fernandes, James Siderius, and Raghav Singal
EC'25 (extended abstract), 2025
[EC]

Churning While Experimenting: Maximizing User Engagement in Recommendation Platforms
Michael Hamilton and Raghav Singal
WINE 2024 (extended abstract), 2026
[WINE]

Counterfactual Analysis in Dynamic Latent State Models
Martin Haugh and Raghav Singal
ICML, 2023
[ICML] [Video] [Press]

Flow-Based Attribution in Graphical Models: A Recursive Shapley Approach
Raghav Singal, George Michailidis, and Hoiyi Ng
ICML (spotlight), 2021
[ICML] [SSRN] [Video]

Shapley Meets Uniform: An Axiomatic Framework for Attribution in Online Advertising
Raghav Singal, Omar Besbes, Antoine Desir, Vineet Goyal, and Garud Iyengar
WWW'19, 2019
[WWW]

A Finite Time Analysis of Temporal Difference Learning with Linear Function Approximation
Jalaj Bhandari, Daniel Russo, and Raghav Singal
COLT (extended abstract), 2018
[COLT]

Contributions to Other Research Projects

Reproducibility in Management Science
Fisar, Greiner, Huber, Katok, Ozkes, and the Management Science Reproducibility Collaboration
Management Science, 2024
Note: Member of the Management Science Reproducibility Collaboration
[Journal] [SSRN]

Teaching

Instructor
Analytics, MBA core (Dartmouth), Rated 5.45/6, 2021 -
Data, Models, and Decisions, MBA elective (Dartmouth), Rated 5.91/6, 2025 -
Optimization Models and Methods, MS (Columbia), Rated 4.50/5, 2019

Co-instructor
Introduction to Algorithms, SHP (Columbia), 2018
Graph Theory by Example, SHP (Columbia), 2018

Case: Analytics in American Football: A New Frontier
C. Daniel Guetta, Raghav Singal, and John Wolfe
Columbia CaseWorks, 2020
Used in the Business Analytics II elective at Columbia Business School

Awards

Finalist in MSOM Service Management SIG Best Paper Award (2025)

MBA Core Teaching Excellence Award, Dartmouth Tuck (2025)

Best 40-Under-40 MBA Professors, Poets&Quants (2025)

Wei-Chung Bradford Hu T'89 Faculty Fellow, Dartmouth Tuck (2023)

2nd place in Michael H. Rothkopf Junior Researcher Paper Prize (2022)

Harvey H. Bundy III T'68 Faculty Fellow, Dartmouth Tuck (2022)

Finalist in RMP Data-Driven Research Challenge (2020)

2nd place in RMP Jeff McGill Student Paper Award (2019) [Press]

Finalist in MIT Sloan Sports Analytics Conference Research Paper Competition (2018)

Highly Commended by The Undergraduate Awards (2015) [Press]

University of Toronto Excellence Award (2013)