Rate My Professor Pankaj Agarwal

Agarwal's research interests center on computational and discrete geometry, encompassing paradigms and techniques, approximation algorithms, stochastic models, geometric optimization, kinetic geometry, data structures, arrangements, proximity problems, triangulation, motion planning, and geometric sampling. He also investigates shape analysis for representation, matching, clustering, and similarity searching; trajectory data analysis including segmentation, matching, clustering, and query processing; GIS applications such as terrain modeling and analysis, navigation, visibility, flow analysis, and ecological modeling; and databases and data mining topics like spatio-temporal databases, query processing, streaming, and automatic fact checking. He has authored books including Intersection and Decomposition Algorithms for Planar Arrangements (1991), Combinatorial Geometry (1995, with J. Pach), and Robotics: The Algorithmic Perspective (1998). Highly cited publications feature Simplification Envelopes (1996, 898 citations), Geometric Range Searching and Its Relatives (1999, 713 citations), Geometric Approximation via Coresets (2005, 621 citations), Exact and Approximation Algorithms for Clustering (2002, 540 citations), and recent works like An Efficient Algorithm for Generalized Polynomial Partitioning and Its Applications (2019) and Flood Risk Analysis on Terrains (2018). With over 29,000 citations and more than 250 scholarly articles, his contributions have profoundly shaped algorithms, geometric computing, and spatial data management.