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Shreyas Sekar

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Shreyas Sekar

Assistant Professor of Operations Management, Rotman School of Management & Department of Management, UTSC.
Faculty Affiliate at the Schwartz Reisman Institute for Technology and Society.

Degrees:

Postdoctoral Fellow, Harvard Business School, 2018-2020
PhD, Computer Science, Rensselaer Polytechnic Institute, 2017
B.Tech Indian Institute of Technology, Roorkee, 2012.

Email:

Send an email to Shreyas Sekar

Personal Website:
https://sekarshre.github.io/

Bio

Shreyas Sekar is an Assistant Professor at the Department of Management, University of Toronto Scarborough with a cross-appointment in the Operations Management and Statistics Area at the Rotman School of Management. Prior to this, he was a Postdoctoral Fellow at the Lab for Innovation Science at the Harvard Business School. His research uses prescriptive, data-driven methodologies to tackle operational challenges arising in online marketplaces, in particular e-commerce platforms. To address such questions, Shreyas draws upon tools from diverse domains including online learning, game theory, combinatorial optimization, and mechanism design. Shreyas received his Ph.D in 2017 at the Rensselaer Polytechnic Institute, where he received the Robert McNaughton prize for the best graduate dissertation in Computer Science.

Selected Publications - Papers

Featured Work

Currently, I am excited by two key questions pertaining to online platforms: 

  1. How can we design optimal, data-driven policies when the underlying data is corrupted due to strategic manipulation or fraudulent behaviour? This is a growing concern among digital platforms due to the rise of paid reviews, fake users, collusion, etc. In recent work, my colleagues and I proposed an online learning algorithm for e-commerce platforms to identify the optimal product ranking even when the underlying data is corrupted by fake users. 
    Media Coverage: Fake online reviews are everywhere. Meet the UTSC prof who’s developing strategies to stop them
     
  2. How should digital platforms design information architectures, i.e., make decisions on the quality, quantity, and order in which information is presented, given that consumers have finite attention online? In a series of papers as well ongoing work, I have sought this address this challenge in a variety of settings:
    --- Product Ranking on e-Commerce Platforms (Collaboration with Wayfair.com)
    --- Travel Time information to drivers on the road
    --- Price disclosure in energy markets
    --- Presenting information to participants in contests (ongoing)

Research and Teaching Interests

Data-Driven Analytics, Revenue Management and Pricing, Digital Marketplaces and Market Design, Online Learning, Information Economics, Decision Making under Uncertainty.

Honors and Awards

  • 2021

    Keynote Speaker, Hashtag Redcarpet Conference, University of Toronto Scarborough

  • 2021

    TD MDAL Grant, TD Management Data and Analytics Lab

  • 2021

    Research Competitiveness Fund, University of Toronto Scarborough

  • 2018

    Finalist, Best paper award, ACM e-Energy Conference

  • 2017

    Robert McNoughton Prize for Best Graduate Dissertation in Computer Science, Rensselaer Polytechnic Insitute

Professional Affiliations/Memberships

  • Schwartz Reisman Institute for Technology and Society

  • Better AI Objectives Group, Vector Institute for Artificial Intelligence

  • Mechanism Design for Social Good