Sanjeev  Khanna

Henry Salvatori Professor
Computer and Information Science (CIS)

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Honors and Awards:  S. Reid Warren Jr. Award - 2010, Guggenheim Fellowship - 2007, IBM Faculty Award - 2007, NSF CAREER Award - 2001, Sloan Research Fellowship - 2000

Research Expertise: Algorithms and Complexity

Sanjeev works in theoretical computer science, studying the amount of resources that are necessary and sufficient to perform a computational task. His specific interests are in fast computation of near-optimal solutions for NP-hard problems, a class which has eluded efficient exact algorithms. Ubiquitous in computer science and related disciplines, some representative examples of this class include multiprocessor scheduling, network design and routing, and the celebrated traveling salesman problem. Sanjeev's recent work has led to efficient algorithms for finding near-optimal solutions to several fundamental network design and routing problems.

Education:
PhD Computer Science - Stanford University - 1996


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