Dr. Sharath Raghvendra’s research interest revolves around the design of algorithms for geometric problems. He is particularly interested in the creation of algorithmic tools and methodologies which are applicable to large-scale, unstructured and potentially very high dimensional geometric data.
Dr. Raghvendra obtained his Ph.D from Duke University. In his Ph.D. dissertation he designed algorithms based on a meaningful and succinct representation of large scale geometric data, for which he won the Best Doctoral Dissertation Award. From 2012 to 2014, he has continued his research as a postdoctoral scholar in the departments of Computer Science and Management Sciences at Stanford University.
Some of his most recent work is applicable to the areas of logistics and data analysis. With respect to logistics, he has designed faster combinatorial algorithms for pickup and delivery problems. He has also established various connections of geometric summaries to clustering, classification and topological data analysis of large-scale and high-dimensional data.
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Granting Institution: NSF