Education

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

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

Papers

Shapley meets uniform: An axiomatic framework for attribution in online advertising
Raghav Singal, Omar Besbes, Antoine Desir, Vineet Goyal, and Garud Iyengar
Major revision in Management Science
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
Minor revision in Operations Research
Extended abstract appeared in COLT, 2018
[arXiv] [COLT]

How to play fantasy sports strategically (and win)
Martin B. Haugh and Raghav Singal
Management Science (accepted)
Finalist in MIT SSAC, 2018
[SSRN] [SSAC] [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]

Talks

Shapley meets uniform: An axiomatic framework for attribution in online advertising
  • INFORMS 2019 (Seattle)
  • YinzOR 2019 (CMU)
  • Condé Nast Data Science (NYC)
  • M&SOM 2019 (Singapore)
  • RM&P 2019 (Stanford)
  • CORS 2019 (Saskatoon)
  • WWW 2019 (San Francisco)
  • POMS 2019 (Washington DC)
  • Yahoo Research Seminar (NYC)
  • Data Science Day 2019 (Columbia)
  • NYC Ops Day 2019 (Columbia)

How to play fantasy sports strategically (and win)
  • POMS 2019 (Washington DC)
  • INFORMS 2018 (Phoenix)
  • CORS 2018 (Halifax)
  • TADC 2018 (LBS)
  • Data Science Day 2018 (Columbia)
  • SSAC 2018 (MIT) [Video]

A Bayesian regression approach to handicapping tennis players based on a rating system
  • CORS 2018 (Halifax)
  • NESSIS 2017 (Harvard)

A Markov decision process-based handicap system for tennis
  • Data Science Social 2016 (Columbia)
  • UTORG 2015 (UToronto)

Teaching

Optimization models and methods (IEOR E4004)
Columbia University
Instructor (Spring 2019)
Around 10 students
Rated 4.50 out of 5
[Info]

Introduction to algorithms (SHP)
Columbia University
Co-instructor (Fall 2018)
Around 50 students
[Info]

Graph theory by example (SHP)
Columbia University
Co-instructor (Spring 2018)
Around 20 students

Optimization models and methods (IEOR E4004)
Columbia University
Teaching assistant (Fall 2015, 2016, 2017)
Around 160 students
Rated 4.63 out of 5

Applied integer programming (IEOR E4600)
Columbia University
Teaching assistant (Spring 2016, 2017)
Around 30 students
Rated 4.49 out of 5

Industry

Adobe
Data scientist intern
June 2017 - August 2017 (San Jose, USA)
Developed models for digital attribution

Ontario Teachers' Pension Plan
Quantitative research co-op
May 2013 - August 2014 (Toronto, Canada)
Worked as a front office quant in the Asset Mix and Risk group

Awards

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
500 West 120th Street
Mudd 315
Columbia University
New York
New York 10027
USA

Email
rs3566 [at] columbia [dot] edu