Anil Damle

Anil Damle is an Assistant Professor in the Department of Computer Science at Cornell University, with affiliations to the Ann S. Bowers College of Computing and Information Science, College of Engineering, and College of Arts and Sciences. His research focuses on numerical linear algebra, computational quantum chemistry, fast algorithms, and machine learning applications. He advises PhD and MS students in these areas and teaches courses like Numerical Analysis and Matrix Computations.

Key research interests include Wannier function localization, matrix perturbation theory, and efficient algorithms for large-scale scientific computing. His work bridges theoretical mathematics and practical applications in physics, statistics, and machine learning.

Recent publications span topics from mortality modeling to transformer compression, reflecting his interdisciplinary approach. He chairs the 2025 Householder Symposium on Numerical Linear Algebra and contributes to open-source tools like the fast kernel transform.