Contributor

Hari Sundar is the Ada Lovelace Associate Professor in the department of computer science at Tufts University. He was previously an Associate Professor in the Kahlert School of Computing at the University of Utah. His research focuses on the development of computationally optimal parallel, high-performance algorithms, that are efficient and scalable on state-of-the-art architectures. It is driven by applications in biosciences, geophysics, computational fluid dynamics and computational relativity. His research has resulted in the development of state-of-the-art distributed algorithms for adaptive mesh refinement, geometric multigrid, fast Gauss transform and sorting. He received his Ph.D. from the University of Pennsylvania and was a postdoctoral scholar at the Oden Institute at the University of Texas at Austin.