Christian Kroer

ASSISTANT PROFESSOR OF INDUSTRIAL ENGINEERING AND OPERATIONS RESEARCH

314 S.W. Mudd 
Mail Code 4721 

Research Interests

equilibrium computation, mechanism design, competitive equilibrium, first-order methods, saddle-point problems, extensive-form games, Stackelberg games, robust optimization, regret minimization, low-rank models

Christian Kroer’s research lies at the intersection of operations research, computer science, and economics. He focuses on sequential game solving, decision making, and market design. A recurring theme in his research is how to solve large-scale problems in practice, and thus he often combines scalable optimization algorithms with data-driven AI methods. His research has applications in areas such as Internet markets (e.g. ad auctions or recommender systems), fair allocation (e.g. of courses to students), security settings (e.g. wi-fi jamming or infrastructure protection), and recreational games (e.g. poker).

Christian Kroer received his Ph.D. in Computer Science from Carnegie Mellon University in 2018. Before coming to Columbia University he spent a year as a postdoc with the Core Data Science group at Facebook Research.

RESEARCH EXPERIENCE

  • Assistant Professor of Industrial Engineering and Operations Research, Columbia University, 2019–
  • Postdoctoral fellow, Facebook Research, 2018-2019

PROFESSIONAL EXPERIENCE

  • Software Developer, Netmester A/s, 2010-2011

HONORS & AWARDS

A complete updated list is available at http://www.columbia.edu/~ck2945/publications.html

  • Computing large market equilibria using abstractions. Christian Kroer, Alexander Peysakhovich, Eric Sodomka, and Nicolas E Stier-Moses. ACM Conference on Economics and Computation (EC), 2019.
  • Pacing Equilibrium in First-Price Auction Markets. Vincent Conitzer, Christian Kroer, Debmalya Panigrahi, Okke Schrijvers, Eric Sodomka, Nicolas Stier-Moses, and Chris Wilkens. ACM Conference on Economics and Computation (EC), 2019.
  • Regret Circuits: Composability of Regret Minimizers. Gabriele Farina, Christian Kroer, and Tuomas Sandholm. International Conference on Machine Learning (ICML), 2019.
  • Faster algorithms for extensive-form game solving via improved smoothing functions. Christian Kroer, Kevin Waugh, Fatma Kılınç-Karzan, and Tuomas Sandholm. Mathematical Programming Series A, 2018
  • Solving Large Sequential Games with the Excessive Gap Technique. Christian Kroer, Gabriele Farina, and Tuomas Sandholm. Neural Information Processing Systems (NIPS), 2018 spotlight presentation.
  • Imperfect-Recall Abstractions with Bounds in Games. Christian Kroer, Tuomas Sandholm. ACM conference on Economics and Computation (EC), 2016.