Anupam Gupta

Anupam Gupta is a Silver Professor of Computer Science at New York University, affiliated with the Courant Institute of Mathematical Sciences. His research focuses on Theoretical Computer Science, particularly Algorithms, Approximation Algorithms, and Metric Embeddings. He holds a Ph.D. in Computer Science from the University of California, Berkeley, and has been recognized for his contributions to the field. Gupta is known for his work on algorithms for uncertain environments, including stochastic and online problems. He has received support from the NSF and the Alfred P. Sloan Research Fellowship. Additionally, he has been honored as an ACM Fellow. His teaching includes graduate courses in approximation algorithms and advanced algorithms, and he has mentored numerous Ph.D. students and postdocs.

Anupam Gupta is a Professor of Computer Science at New York University, specializing in Theoretical Computer Science. His research focuses on algorithm design, optimization, and data privacy, with applications in network design, submodular optimization, and differential privacy. He has published extensively on topics such as stochastic bandits, private data release, and low-distortion graph embeddings. His work addresses challenges in computational complexity, approximation algorithms, and the efficient management of large-scale data. Gupta's contributions span both theoretical and applied domains, emphasizing the development of robust and scalable solutions for complex computational problems.