Debarati Das

Debarati Das is an Assistant Professor in Computer Science and Engineering, specializing in Clustering Algorithms, Edit Distance, and Approximation Algorithms. Her research focuses on theoretical computer science, particularly in algorithm design for data streams, permutation clustering, and sequence alignment.

• Grants: NSF CAREER Award (2024), NSF Student Travel Grant (2023).

Her work includes breakthroughs in consensus clustering, achieving sub-2-approximation, and developing space-efficient algorithms for edit distance in distributed models. Recent projects explore dynamic shortest paths in planar graphs and pseudorandomness extraction.

Her publications span journals like the Journal of the ACM and conferences such as SODA, STOC, and FOCS. Collaborations include researchers from institutions in the U.S. and Europe, with applications in computational biology and parallel computing.