Upcoming Talks

Beyond Myopia: Model-free Approximate Bayesian Learning for Conversion Funnel Optimization
  • Marketing Science: June 5, 9-10am EDT
  • MARBLE (KDD): Aug 15, 1-1:30pm EDT

Flow-based Attribution in Graphical Models: A Recursive Shapley Approach
  • CORS: June 7, 3:30-5pm EDT
  • ICML: July 22, 10:40-10:45am EDT

Mechanism Design for Workforce Scheduling in On-demand Transportation
  • MSOM: June 8, 9:30-10am EDT
  • CORS: June 9, 10-11:30am EDT
  • RMP: June 29, 9-10am EDT
  • INFORMS: Oct 24, 9-10:30am EDT

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)

Papers

Flow-based Attribution in Graphical Models: A Recursive Shapley Approach
Raghav Singal, George Michailidis, and Hoiyi Ng
Journal version in preparation
Preliminary version appeared in ICML, 2021
[SSRN] [ICML]

Shapley Meets Uniform: An Axiomatic Framework for Attribution in Online Advertising
Raghav Singal, Omar Besbes, Antoine Desir, Vineet Goyal, and Garud Iyengar
Management Science, forthcoming
Preliminary version appeared in WWW, 2019
2nd place in INFORMS RMP Student Paper Award, 2019
[SSRN] [WWW]

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]

How to Play Fantasy Sports Strategically (and Win)
Martin B. Haugh and Raghav Singal
Management Science, 2020
Finalist in MIT SSAC, 2018
[Journal] [SSRN] [Video]

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]

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]

Teaching

Instructor
Analytics, MBA (Dartmouth), Fall 2021
Optimization Models and Methods, MS (Columbia), Rated 4.50/5, Spring 2019

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

Industry

Amazon
Data Scientist Intern
October 2020 - June 2021 (NYC/Seattle, USA)
Developed models for attribution in supply chain

Adobe
Data Scientist Intern
June 2017 - August 2017 (San Jose, USA)
Developed models for attribution in online advertising

Ontario Teachers' Pension Plan
Quantitative Research Co-op
May 2013 - August 2014 (Toronto, Canada)
Worked as a front office quant

Awards

Finalist in RMP Data-Driven Research Challenge (2021)

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

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

Outstanding Teaching Assistant Award at Columbia University (2018)

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

Best Poster Award at MIE Research Symposium (2015)

MIE Summer Award at University of Toronto (2015)

University of Toronto Excellence Award (2013)

Contact

Mailing address
Raghav Singal
100 Tuck Hall
Chase 304
Tuck School of Business
Hanover NH 03755 USA

Email
singal [at] dartmouth [dot] edu