Yuri Faenza


334 S.W. Mudd

Tel(212) 854-4703

Yuri Faenza works on the theory and applications of Optimization. He is primarily interested in the interplay of mathematical programming and computer science, in order to construct and solve mathematical models that support decision making.

Research Interests

Mathematical Programming, Combinatorial Optimization, Polyhedral Combinatronics, Market Design
In particular, Faenza’s research focuses on Discrete Optimization, including Integer Programming and extensions (for instance, knapsack problems), combinatorial optimization (for instance, matching problems), and polyhedral combinatorics (for instance, extended formulations), and their application to real-world problems such as two-sided markets and multi-period investments planning, among others. 
Faenza received a BSc in management science and engineering, summa cum laude, in 2004 and an MSc in mathematical engineering, summa cum laude, in 2006 from the Università di Roma Tor Vergata, Italy. He received a PhD in operations research from the Sapienza University of Rome, Italy, in 2010. He was a Swiss National Science Foundation Ambizione Fellow at the École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, 2015–2016, and has been a postdoctoral researcher at the University of Brussels, Belgium, 2014; at EPFL, Switzerland, 2012–2014; and at the University of Padua, Italy, 2010–2012. 


  • Visiting Researcher, Online and matching-based Markets, Simons Institute, UC Berkeley, 2019
  • Visiting Researcher, HIM, Germany, 2015
  • Postdoctoral Researcher, Mathematics, ULB, Belgium, 2014
  • Postdoctoral Researcher, DISOPT group, EPFL, Switzerland, 2012–2014
  • Postdoctoral Researcher, Mathematics, University of Padua, Italy, 2010–2012
  • Visiting Researcher, Combinatorics and Optimization, University of Waterloo, Canada, 2010
  • Visiting Researcher, Discrete Optimization group, ZIB, Germany, 2006 


  • Associate Professor, Industrial Engineering and Operations Research, Columbia University, from 2022 (Affiliated  with the Data Science Institute, 2019-)
  • Assistant Professor, Industrial Engineering and Operations Research, Columbia University, 2016-2021
  • SNSF Ambizione Fellow, DISOPT group, EPFL, Switzerland, 2015 – 2016


  • SIAM


  • Meta Research Award, 2022 
  • CAREER Award, NSF, 2021
  • Office of Naval Research Grant, 2020
  • I-Corps Grant, NSF, 2019 
  • Gift by the Swiss National Science Foundation, 2017
  • Swiss National Science Foundation Ambizione Grant, 2014


  • CAREER Award, NSF, 2021
  • Distinguished Faculty Teaching Award, The Fu Foundation School of Engineering, Columbia University, 2018
  • Lorenzo Brunetta award for a PhD thesis in Operations Research, 2012 


  • Y. Faenza, D. Segev, and L. Zhang. Approximation algorithms for the generalized incremental knapsack problem. Mathematical Programming 198(1), pp. 27-83 (2023)
  • Y. Faenza and X. Zhang. A nely representable lattices, stable matchings, and choice functions. Mathematical Programming 197(2), pp. 721-760 (2023)
  • Y. Faenza and T. Kavitha. Quasi-popular matchings, optimality, and extended formulations. Mathematics of Operations Research, 47(1), pp. 427-457 (2022)
  • Y. Faenza and X. Zhang. Legal Assignments and fast EADAM with consent via classical theory of stable matchings. Operations Research 70(3), pp. 1873-1890 (2022)
  • Y. Faenza, G. Oriolo, and G. Stauffer. Separation routine and extended formulations for the stable set problem in claw-free graphs. Mathematical
    Programming 188, pp. 53-84 (2021)
  • M. Aprile and Y. Faenza. Extended formulations from communication protocols in output-efficient time. Mathematical Programming, 183, pp. 41-59 (2020)
  • Y. Tang, S. Agrawal, and Y. Faenza. Reinforcement Learning for Integer Programming: Learning to Cut. Proceedings of 37th International Conference on Machine Learning (ICML), pp. 9367-9376 (2020)
  • M. Conforti, M. Di Summa, and Y. Faenza. Balas formulation for the union of polytopes is optimal. Mathematical Programming, 180, pp. 311-326 (2020)
  • Y. Faenza, T. Kavitha, V. Powers, and X. Zhang. Popular Matchings and Limits to Tractability. Proceedings of the 30th ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 2790-2809 (2019)
  • Y. Faenza, S. Fiorini, R. Grappe, and H.R. Tiwary. Extended formulations, non-negative factorizations, and randomized communication protocols, Mathematical Programming, 153-1 (2015)
  • Y. Faenza, G. Oriolo, and G. Stauffer. Solving the weighted stable set problem in claw-free graphs via decomposition, Journal of the ACM, 61-4: 20 (2014)