Chamsi Hssaine

Chamsi Hssaine

Postdoctoral Scientist,
Amazon

I am a postdoctoral scientist at Amazon within the Supply Chain Optimization Technologies (SCOT) group. I will join the Department of Data Sciences and Operations at USC’s Marshall School of Business as an assistant professor in Fall 2023.

My research lies at the intersection of operations research and economics, focusing on algorithm and incentive design for smart societal systems. More specifically, I am interested in developing tools for these people-centric systems, with an emphasis on incorporating more realistic models of behavior under incentives.

I obtained my Ph.D. in Operations Research at Cornell University, where I was fortunate to be advised by Professor Siddhartha Banerjee. Prior to that, I obtained my B.S.E. in Operations Research and Financial Engineering from Princeton University, with a minor in Applied Mathematics.

Interests

  • Data-Driven Decision-Making
  • Revenue Management and Pricing

Education

  • Ph.D., Operations Research, 2022

    Cornell University

  • M.S., Operations Research, 2020

    Cornell University

  • B.S.E., Operations Research and Financial Engineering, 2016

    Princeton University

Recent & Upcoming Talks

Balls-into-Bins and The Power of Flexibility in Load Balancing Systems:

  • Amazon, Promise Research Meeting, December 2022

Pseudo-Competitive Games and Algorithmic Pricing:

  • Rotman Young Scholar Seminar Series, University of Toronto Rotman School of Management OM Department, September 2022
  • Workshop on Algorithms for Learning and Economics, June 2022
  • Meta, April 2022
  • INFORMS Annual Meeting, October 2021
  • Cornell ORIE Young Researchers Workshop, October 2021
  • Cornell CS Theory Seminar, September 2021
  • 31st European Conference on Operational Research, July 2021
  • INFORMS Revenue Management and Pricing Conference, June 2021
  • Marketplace Innovation Workshop (Poster), May 2021

Teaching

I have been a teaching assistant for the following courses:

  • ORIE 4580: Simulation (Fall 2018)
  • ORIE 3800: Information Systems Analysis (Spring 2017-2018)
  • ORIE 3500: Engineering Probability and Statistics II (Fall 2016)

Contact