Algorithms, Combinatorics, and Optimization Program
Carnegie Mellon University

Carnegie Mellon University has taken the initiative of offering an interdisciplinary Ph.D program in Algorithms, Combinatorics, and Optimization. It is administered jointly by the Tepper School of Business (Operations Research group), the Computer Science Department (Algorithms and Complexity group), and the Department of Mathematical Sciences (Discrete Mathematics group).

More About the Program Admission/Application Information
Ph.D. Program Requirements ACO Seminar


Egon Balas (deceased) Polyhedral combinatorics, combinatorial optimization.
Nina Balcan machine learning, computational aspects in economics and game theory, algorithms
Guy Blelloch Parallel algorithms and languages.
Avrim Blum Machine learning, approximation and on-line algorithms, AI planning.
Manuel Blum (Emeritus) Complexity Theory, cryptography, program checking.
Thomas A. Bohman Extremal Combinatorics.
Boris Bukh Combinatorial geometry, combinatorial number theory.
Gérard Cornuéjols Combinatorial optimization, graph theory, integer programming.
Alan Frieze Average case analysis of algorithms, combinatorics.
Florian Frick Geometric and topological methods.
Irina Gheorghiciuc Combinatorics.
Anupam Gupta Approximation algorithms, metric embeddings, network algorithms.
Venkatesan Guruswami Coding theory, Approximation Algorithms and Hardness of Approximations, Complexity Theory.
Bernhard Haeupler Design and analysis of combinatorial algorithms, distributed algorithms, information theory.
Mor Harchol-Balter Queueing theory, stochastic modeling, probability theory, heavy-tailed workloads, Web servers, networking.
John Hooker Operations research techniques in logic, artificial intelligence.
Fatma Kılınç-Karzan Convex optimization, large-scale algorithms, decision making under uncertainty.
Po-Shen Loh Probabilistic and Extremal Combinatorics, and applications to Theoretical Computer Science.
Gary Miller Algorithm design, parallel algorithms, scientific computing.
Benjamin Moseley Design, analysis and evaluation of algorithms.
Ryan O'Donnell Complexity theory, analysis of boolean functions, approximation hardness.
Javier Peña Theory and algorithms for convex optimization, numerical analysis.
Wesley Pegden Combinatorics, Abelian Sandpile problem
R. Ravi Approximation algorithms, combinatorial optimization, computational biology.
Steven Rudich Complexity theory, cryptography, combinatorics.
Tuomas Sandholm Market design, game theory, optimization (integer programming, search, stochastic optimization,
Daniel Sleator Data structures, algorithms, parsing.
Richard Statman Theory of computation, symbolic computation.
Michael Trick Computational integer and combinatorial optimization, applications in sports and the social sciences.
Willem Van Hoeve Combinatorial optimization; constraint programming; mathematical programming; integration of constraint programming and mathematical programming.
Computer Science
  Blue Ball Mathematical Sciences
  Green Ball Operations Research


Charles Argue
Da Qi Chen
Ting-Wei Chao
Daniel De Roux
Zichao Dong
Mihir Hasabnis
Daniel Hathcock
Jakob Hofstad
Su Jia
Anthony Karahalios
Thomas Lavastida
Roie Levin
Jason Li
Heather Newman
Aditya Raut
Andrii Riazanov
Oleksandr Rudenko
Sherry Sarkar
Anish Sevekari
Amirbehshad Shahrasbi
Lingqing Shen
Matthew Superdock
Ziye Tang
Ananya Uppal
Zoe Wellner
Weizhong Zhang
Rudy Zhou
Mik Zlatin

Recent Graduates

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General questions or suggestions, please contact: Alan Frieze or Avrim Blum