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Nisheeth Vishnoi is a Professor at Yale University, specializing in theoretical computer science. His research spans several key areas, including approximability of NP-hard problems, as well as both combinatorial and convex optimization. He addresses algorithmic questions related to dynamical systems and stochastic processes, with a broad interest in understanding how theoretical computer science intersects with societal issues. Currently, his focus is on natural algorithms and the emergence of intelligence, exploring critical questions at the interface of artificial intelligence, ethics, and society. Vishnoi has received numerous awards for his contributions to the field, including the Technical Paper Award from ACM FAT* in 2019 and the IIT Bombay Young Alumni Achievers Award in 2016. His influential publications include works on algorithmic approaches to polarization and personalization, as well as advancements in Hamiltonian Monte Carlo methods. He holds a Ph.D. from the Georgia Institute of Technology and a B.Tech from the Indian Institute of Technology Bombay.
Administered via the Graduate School of Arts and Sciences (GSAS). GRE General is optional for PhD.