Padma Raghavan

Education

Ph.D., Computer Science, Pennsylvania State University

M.S., Computer Science, Pennsylvania State University

B.Tech., Computer Science and Engineering, Indian Institute of Technology

About

Padma Raghavan is the Chancellor’s executive director for science and technology strategy and Distinguished Professor of Computer Science at Vanderbilt University. In this role, Raghavan develops strategy and models as part of the Chancellor’s growth initiatives, such as the establishment of the Institute for Quantum Innovation with EPB Chattanooga.

Prior to taking on this role, Raghavan served as the Vice Provost for Research and Innovation and Chief Research Officer, where she oversaw a major expansion of the university’s research, including new models for partnerships such as Ancora Innovation with Deerfield Management, to accelerate the development of life-changing therapeutics, and Pathfinder with the U.S. Army, to rapidly develop and deploy mission-critical technology solutions.

As a faculty member, Raghavan has been recognized for her contributions to supercomputing as a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) and a Fellow of American Association for the Advancement of Science (AAAS). Raghavan currently serves on UT-Battelle’s Board of Governors and was appointed to the President’s Committee on the National Medal of Science in 2022.

Before joining Vanderbilt in 2016, Raghavan was Distinguished Professor of Computer Science and Engineering and Associate Vice President for Research and Strategic Initiatives at Pennsylvania State University. Raghavan also served as the founding director of Penn State’s Institute for Computational and Data Sciences, responsible for advancing high-performance computing for interdisciplinary research university-wide.

Research Focus

High-performance computing (HPC) & supercomputing, Computational & data science for scientific modeling, Parallel algorithms for sparse matrices and graphs

Publication Highlights

A Cartesian parallel nested dissection algorithm
MT Heath, P Raghavan
SIAM Journal on Matrix Analysis and Applications 16 (1), 235-253
https://scholar.google.com/citations?view_op=view_citation&hl=en&user=JDctypMAAAAJ&citation_for_view=JDctypMAAAAJ:u5HHmVD_uO8C

Realizing the potential of data science
F Berman, R Rutenbar, B Hailpern, H Christensen, S Davidson, D Estrin, …
Communications of the ACM 61 (4), 67-72
https://scholar.google.com/citations?view_op=view_citation&hl=en&user=JDctypMAAAAJ&citation_for_view=JDctypMAAAAJ:hSRAE-fF4OAC

Research and education in computational science and engineering
U Rude, K Willcox, LC McInnes, HD Sterck
Siam Review 60 (3), 707-754
https://scholar.google.com/citations?view_op=view_citation&hl=en&user=JDctypMAAAAJ&citation_for_view=JDctypMAAAAJ:wvYxNZNCP7wC