Ph.D., Computer Science
M.S., Computer Science
B.Tech., Computer Science and Engineering
Indian Institute of Technology
Professor of Computer Science and Computer Engineering
Raghavan's research predominantly concerns enhancing the parallel
performance, energy efficiency and reliability of computations that
involve high-dimensional sparse and unstructured data including
matrices, and graphs. Sparse representations of data arise from many
different contexts, for example, from largely local connections in a
system represented as a sparse graph or network or from partial
differential equations models where the number of nonzeroes in an
associated matrix is bounded by a small constant times its dimension.
Algorithms that exploit sparsity can deliver performance improvements by
constant factors to orders of magnitude. Consequently, they enable the
solution of larger or more complex problems for computation and
data-enabled science and engineering "at scale" in a variety of
Padma Raghavan is a Professor of Computer Science in the Department of Electrical Engineering and Computer Science at Vanderbilt University, where she is also Vice Provost for Research. Prior to joining Vanderbilt in February 2016, she was a Distinguished Professor of Computer Science and Engineering at the Pennsylvania State University and served as the Associate Vice President for Research and Director of Strategic Initiatives, in addition to being the founding Director of the Institute for CyberScience, the coordinating unit on campus for developing interdisciplinary computation and data-enabled science and engineering and the provider of high-performance computing services for the university.
Raghavan specializes in high-performance computing and computational science and engineering. In her professorial role, Raghavan is deeply involved in education and research, with 46 Masters and Ph.D. theses supervised and approximately 100 peer-reviewed publications in three areas: scalable parallel computing; energy-aware supercomputing; computational modeling and knowledge extraction. She has earned several awards including an NSF CAREER Award (1995), the Maria Goeppert-Mayer Distinguished Scholar Award (2002, University of Chicago and the Argonne National Laboratory), and selection as an IEEE Fellow (2013).
Raghavan serves on several editorial boards including those at SIAM (Society of Industrial and Applied Mathematics) and IEEE (Institute of Electrical and Electronics Engineers): SIAM Series on Computational Science and Engineering; SIAM Series on Software Environments and Tools; Journal of Parallel and Distributed Computing; and the IEEE Transactions on Parallel and Distributed Systems. Recently Raghavan co-chaired Technical Papers at Supercomputing 2012, and the 2011 SIAM Conference on Computational Science and Engineering. She also serves on various advisory and review panels: the National Research Council's Committee on Future Directions for NSF Advanced Computing Infrastructure; the National Academies Panel on Information Science at the Army Research Laboratory; the review committee for the Computation Directorate at the Lawrence Livermore National Laboratory; the Board of Trustees of the Great Lakes Consortium for Petascale Computing; and the Computer Research Association's Committee on the Status of Women in Computing.