Theory of Computing

The theory of computing is the study of efficient computation, models of computational processes, and their limits. Research at Cornell spans all areas of the theory of computing and is responsible for the development of modern computational complexity theory, the foundations of efficient graph algorithms, and the use of applied logic and formal verification for building reliable systems. In keeping with our tradition of opening new frontiers in theory research, we have emerged in recent years as a leader in exploring the interface between computation and the social sciences.

In addition to its depth in the central areas of theory, Cornell is unique among top research departments in the fluency with which students can interact with faculty in both theoretical and applied areas, and work on problems at the critical juncture of theory and applications.

Faculty

Robert Constable Type theory and automated reasoning.	Joe Halpern Reasoning about knowledge and uncertainty, distributed computing, causality, security, game theory.
Juris Hartmanis Computational complexity theory.	John Hopcroft Algorithms, information capture and access, random graphs and spectral methods.
Bobby Kleinberg Algorithms, game theory, learning, and networks.	Jon Kleinberg Algorithms, social and information networks.
Dexter Kozen Computational complexity, program logic and semantics, computational algebra.	Rafael Pass Cryptography and its interplay with computational complexity and game theory.
David Shmoys Approximation algorithms, computational sustainability.	David Steurer Algorithms and complexity theory, hardness of approximation, SDP rounding.
Eva Tardos Algorithms, algorithmic game theory.	David Williamson Approximation algorithms, information networks.

Seminars

Faculty

Postdocs

Visitors

Ph.D. Students

Courses