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

Faculty

Egon Balas	Polyhedral combinatorics, combinatorial optimization.
Guy Blelloch	Parallel algorithms and languages.
Avrim Blum	Machine learning, approximation and on-line algorithms, AI planning.
Manuel Blum	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.
Irina Gheorghiciuc	Combinatorics.
Anupam Gupta	Approximation algorithms, metric embeddings, network algorithms.
Venkatesan Guruswami	Coding theory, Approximation Algorithms and Hardness of Approximations, Complexity 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	Optimization, compressed sensing.
John Lafferty	Speech and natural language processing, statistical learning algorithms, information theory.
Po-Shen Loh	Probabilistic and Extremal Combinatorics, and applications to Theoretical Computer Science.
Bruce Maggs	Parallel algorithms and architectures, computer networks.
François Margot	Integer Linear Programming, Polyhedral Combinatorics, Enumeration Problems.
Gary Miller	Algorithm design, parallel algorithms, scientific computing.
Ryan O'Donnell	Complexity theory, analysis of boolean functions, approximation hardness.
Javier Peña	Theory and algorithms for convex optimization, numerical analysis.
Ariel Procaccia	Computational game theory, mechanism design, and computational social choice
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.

Key:

Computer Science
Department

Operations
Research Group

Department of
Mathematical Sciences

Students

Deepak Bal
Patrick Bennett
David Bergman
Xi Chen
Stylianos Despotakis
Lisa Espig
Jenny Iglesias
Livia Ilie
Nate Ince
Jeremy Karp
Aleksandr M. Kazachkov
Brian Kell
Misha Lavrov
Qihang Lin
Marco Molinaro
Marla Slusky
Christian Tjandraamadja

Charalampos (Babis) Tsourakakis with Alan Frieze	Probability on graphs, randomized algorithms, spectral graph theory and machine learning
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