Prof. Shekhar is a leading researcher in the area of spatial data mining (SDM), and spatial databases (SDB), interdisciplinary areas at the intersection of Computer Science and Geographic Information Sciences (GIS). Major contributions in SDM include the notion of co-location patterns in spatial datasets, characterization of the computational structure of spatial outlier detection, faster algorithms for estimating parameters for the spatial auto-regression model, as well one of the most scalable parallel formulation of the back-propagation learning algorithms for neural networks. Major contributions in SDB include the Connectivity-Clustered Access Method (CCAM), a new storage and access method for spatial networks, which outperform traditional indexes (e.g. R-tree family) in carrying out network computations. Other contributions relate to with semantic query optimization and high performance geographic databases.

Prof. Shekhar was elected an IEEE Fellow and received the IEEE Technical Achievement Award for contributions to spatial database storage methods, data mining, and GIS. He has a distinguished academic record that includes 200+ refereed papers and two books including a textbook on Spatial Databases (Prentice Hall, 2003, ISBN 0-13-017480-7). He is serving as a member of the mapping science committee of the NRC/NAS (National Research Council National Academy of Sciences) (2004-9), and the steering committee of the ACM Symposium on Geographic Information Systems. He is also serving as a co-Editor-in-Chief of Geo-Informatica: An Intl. Journal on Advances in Computer Sc. for GIS. He has served as a member of the NRC/NAS Committee to review basic and applied research at National Geo-spatial-Intelligence Agency (NGA), the Board of Directors of University Consortium on GIS (2003-4), the editorial boards of IEEE Transactions on Knowledge and Data Engineering as well as the IEEE-CS Computer Science & Eng. Practice Board. He served as a program co-chair of the ACM Intl. Workshop on Advances in GIS (1996).