Raghav Singal

Bounding Counterfactuals in Hidden Markov Models
  • Dartmouth CS (Hanover): Mar 1, 12-1:30pm
  • Berkeley IEOR (Berkeley): Apr 15
  • POMS (Minneapolis): Apr 28, 4:30-6pm

Online Matching with Heterogeneous Supply and Minimum Allocation Guarantees
  • Wharton (Philadelphia): Apr 23
  • POMS (Minneapolis): Apr 28, 2:45-4:15pm

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)

Bounding Counterfactuals in Hidden Markov Models and Beyond
Martin Haugh and Raghav Singal
Working paper
Preliminary version appeared in ICML, 2023
[SSRN] [ICML] [Video] [Press]

Churning While Experimenting: Maximizing User Engagement in Recommendation Platforms
Michael Hamilton and Raghav Singal
Working paper
Finalist in INFORMS RMP Data-Driven Research Challenge, 2020
[SSRN]

Workforce Scheduling with Heterogeneous Time Preferences: Effective Wages and Workers Supply
Omar Besbes, Vineet Goyal, Garud Iyengar, and Raghav Singal
Minor revision in Manufacturing & Service Operations Management
2nd place in Rothkopf Junior Researcher Paper Prize, 2022
Spotlight at RMP and MSOM, 2022
[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 (forthcoming)
[Journal] [arXiv] [Code]

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]

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
Preliminary version appeared in WWW, 2019
2nd place in INFORMS RMP Student Paper Award, 2019
[Journal] [SSRN] [WWW] [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]

How to Play Fantasy Sports Strategically (and Win)
Martin Haugh and Raghav Singal
Management Science, 2021
Finalist in MIT SSAC, 2018
[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
Extended abstract appeared in COLT, 2018
[Journal] [arXiv] [COLT]

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]

Instructor
Analytics, MBA (Dartmouth), Rated 5.37/6, 2021, 2022, 2023
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

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

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

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

Finalist in RMP Data-Driven Research Challenge (2021)

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

Cheung-Kong Graduate School of Business (CKGSB) Fellowship (2018) [Press]

Outstanding Teaching Assistant Award at Columbia University (2018)

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

University of Toronto Excellence Award (2013)