Upcoming

How to play fantasy sports strategically (and win)
Martin B. Haugh and Raghav Singal
INFORMS Annual Meeting (Phoenix, USA)
Phoenix Convention Center (North Bldg 232C)
Nov 4, 2018 from 12 p.m. to 12:30 p.m.
[Link]

Education

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

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

Papers

A finite time analysis of temporal difference learning with linear function approximation
Jalaj Bhandari, Daniel Russo, and Raghav Singal
COLT, 2018 (extended abstract)
[COLT]

How to play fantasy sports strategically (and win)
Martin B. Haugh and Raghav Singal
MIT Sloan Sports Analytics Conference, 2018
[PDF] [Sloan] [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

How to play fantasy sports strategically (and win)
Martin B. Haugh and Raghav Singal
  • CORS Annual Conference (Halifax, Canada), June 2018
  • TADC, London Business School (London, UK), May 2018
  • Data Science Day, Columbia University (NYC, USA), March 2018 (poster)
  • MIT Sloan Sports Analytics Conference (Boston, USA), February 2018 [Video]
  • IEOR, Columbia University (NYC, USA), September 2016

A Bayesian regression approach to handicapping tennis players based on a rating system
Timothy C. Y. Chan and Raghav Singal
  • CORS Annual Conference (Halifax, Canada), June 2018
  • NESSIS, Harvard University (Boston, USA), September 2017 (poster)

A Markov Decision Process-based handicap system for tennis
Timothy C. Y. Chan and Raghav Singal
  • Data Science Institute, Columbia University (NYC, USA), October 2016 (poster)
  • UTORG, University of Toronto (Toronto, Canada), June 2015

Improving CBCT image quality using modified shading correction, selective regression, and mathematical programming
Dionne M. Aleman, Douglas Moseley, and Raghav Singal
  • MIE Research Symposium, University of Toronto (Toronto, Canada), June 2015
  • IIE Annual Conference (Nashville, USA), June 2015
  • IMNO (London, Canada), March 2015 (poster)
  • IIE Annual Conference (Montreal, Canada), May 2014

Teaching

Introduction to algorithms
Columbia University (Science Honors Program)
Instructor (Fall 2018)
Around 50 students

Graph theory by example
Columbia University (Science Honors Program)
Instructor (Spring 2018)
Around 20 students

IEORE4004 Optimization models and methods
Columbia University
Teaching assistant (Fall 2015, 2016, 2017)
Around 160 students
Rated 4.63 out of 5

IEORE4600 Applied integer programming
Columbia University
Teaching assistant (Spring 2016, 2017)
Around 30 students
Rated 4.49 out of 5

Industry

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

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

Awards

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 at MIE Research Symposium (2015)

MIE Summer Award at University of Toronto (2015)

Dan Cornacchia/Ernst and Young Scholarship (2013)

University of Toronto Excellence Award (2013)

Contact

Mailing address
Raghav Singal
500 West 120th Street
Mudd 315
Columbia University
New York City
New York 10027
USA

Email
rs3566 [at] columbia [dot] edu