Aleksandr M. Kazachkov

About

I am an assistant professor in the Department of Industrial & Systems Engineering at the University of Florida (UF), where I also serve as an assistant director of the Center for Applied Optimization. Previously I was a postdoctoral researcher under Andrea Lodi at Polytechnique Montréal. I received my Ph.D. in Algorithms, Combinatorics, and Optimization from Carnegie Mellon University in May 2018, under Egon Balas.

My work has been supported by the Air Force Office of Scientific Research, the National Science Foundation, and the UF Informatics Institute.

You can find more information about me and my recent research on my CV. Please contact me if you have any questions about my work.

Updates (click to show / hide)

Mar 2026 Part of the guest editorial team for a special issue of the INFORMS Journal on Optimization for the 2026 INFORMS Optimization Society Conference.
Mar 2026 Co-chaired (with Joe Paat) the refereed proceedings at the 2026 INFORMS Optimization Society Conference (IOS 2026), held March 20-22, 2026 in Atlanta, GA.
Jul 2025 Joined the editorial board of Mathematical Programming Computation.
Jun 2025 Chaired the program committee for the 2025 Mixed Integer Programming Workshop in Minneapolis, Minnesota.
Mar 2025 Honored to receive a CAREER (Faculty Early Career Development Program) Award from the National Science Foundation (NSF), titled CAREER: Disjunctive Cutting Plane Selection via Machine Learning for Mixed Integer Programming.
Jun 2024 Served on the program committee for the 2024 Mixed Integer Programming Workshop in Lexington, Kentucky.
Mar 2024 Joined the editorial board of the INFORMS Journal on Computing.
Jul 2023 Received a grant from the Air Force Office of Scientific Research on Efficiently Strengthening Disjunctive Cutting Planes.
Feb 2022 Joined the editorial board of the Computational Optimization and Applications.
Sep 2021 Added role as an assistant director of the Center for Applied Optimization.
Jan 2021 Started position as an assistant professor at UF ISE.
Apr 2020 Began organizing virtual Discrete Optimization Talks (DOTs) with Elias B. Khalil.
Old news I founded the INFORMS Student Chapter at CMU, which I encourage the CMU community to join. The chapter has been recognized several times by INFORMS for its activities. I was also the founding chair of the YinzOR Student Conference, an annual student-led conference organized by CMU INFORMS.

Research

My research focuses on the methodology and applications of discrete optimization, including improving integer programming techniques and designing fair mechanisms for the allocation of indivisible resources. I am also interested in exploring the opportunities and limitations of machine learning in optimization solvers. The motivating applications for my research tend to be prosocial, such as from nonprofit, healthcare, and public sectors.

Cutting Plane Methods

The Strength of Root Cuts in an Extended Abstract Branch-and-Cut Model. With B. Han. Conference on Integer Programming and Combinatorial Optimization, 2026.
V-Polyhedral Disjunctive Cuts. With E. Balas. Mathematical Programming, 2026. Winner of the INFORMS Computing Society Student Paper Award at the 2018 INFORMS Annual Meeting. The associated talk is V-polyhedral disjunctive cuts.
Monoidal Strengthening of Simple V-Polyhedral Disjunctive Cuts. With E. Balas. Mathematical Programming, 2025. Supercedes the IPCO 2023 version.
An Abstract Model for Branch and Cut. With P. Le Bodic and S. Sankaranarayanan. Mathematical Programming, 2024. Supercedes the IPCO 2022 version.
Cutting Plane Generation Through Sparse Principal Component Analysis. With S. Dey, A. Lodi, G. Muñoz. SIAM Journal on Optimization, 2022.
Partial Hyperplane Activation for Generalized Intersection Cuts. With E. Balas, F. Margot, S. Nadarajah. Mathematical Programming Computation, 2020. Previously appeared as a poster, Computational investigation of generalized intersection cuts, at the Mixed Integer Programming Workshop in 2014, where it won the Best Poster Prize.

Computational Economics

Symmetrically Fair Allocations of Indivisible Goods. With C. Johnston. Working paper, 2024.
On Tanking and Competitive Balance: Reconciling Conflicting Incentives. With S. Vardi. Working paper. An earlier version was peer reviewed and presented at the Conference on Algorithmic Decision Theory in October 2019.
Fair and Efficient Online Allocations. With G. Benadè, A.D. Procaccia, A. Psomas, and D. Zeng. Operations Research, 2024.
How to Make Envy Vanish Over Time. With G. Benadè, A.D. Procaccia, and C.-A. Psomas. ACM Conference on Economics and Computation, 2018.
Small Representations of Big Kidney Exchange Graphs. With J.P. Dickerson, A.D. Procaccia, and T. Sandholm. AAAI Conference on Artificial Intelligence, 2017. Previously presented at EXPLORE workshop at AAMAS 2016, where it was awarded Most Visionary Paper.
Envy-Free Division of Sellable Goods. With J. Karp and A.D. Procaccia. AAAI Conference on Artificial Intelligence, 2014.
Guessing Preferences: A New Approach to Multi-Attribute Ranking and Selection. With P.I. Frazier. Winter Simulation Conference, 2011.

Students

Mohammad Amini (coadvised with Mostafa Reisi)
Zixuan Feng
Boyang Han
Connor Johnston

The next deadline to apply to the UF ISE PhD program is December 5, 2026, for Fall 2027 admission. This is a priority deadline, and it is necessary to apply by this date to be considered for our Spring Visit weekend. However, you will still be able to apply until January 15, 2027. (There is also a chance to apply for "off-cycle" Spring 2027 admission.)

Please be aware that (in our department) applications are first reviewed by a committee, who make an admission decision. Afterwards, individual faculty members can offer funding for your PhD; typically, students secure funding before accepting a PhD offer. I schedule interviews with prospective PhD candidates to my group through early March, after initial decisions are made by the admissions committee.

Some of the courses / skills that would be helpful for a researcher working with me: writing proofs formally, linear algebra / matrix analysis, real analysis, convex analysis, linear programming, integer programming, graph theory, computer programming (C++ / Python / Julia), software engineering (or at least familiarity with version control such as GitHub). Lastly, producing research also involves communicating results clearly, so it is helpful to know and follow good practices with LaTeX, writing, and speaking. All members of the research team are accepted based on merit (based on technical skills + research alignment) but applications are encouraged from people of all backgrounds.