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Raju Vatsavai

Associate Director of Spatial Computing and Technology
Office Phone: 919-515-6019


Biography

Raju is a Chancellor’s Faculty Excellence Program Cluster Associate Professor in Geospatial Analytics in the Department of Computer Science. As the Center’s Associate Director of Spatial Computing & Technology, Raju plays a leadership role in our strategic vision for spatial computing research. He works at the intersection of big data management, data analytics, and high performance computing with applications in national security, geospatial intelligence, natural resources, climate change, location-based services, and human terrain mapping. Raju was previously the lead data scientist for the computational sciences and engineering division of the Oak Ridge National Laboratory (ORNL). He holds MS and PhD degrees in computer science from the University of Minnesota and is coming to NC State with more than 20 years of research and development experience in large-scale spatiotemporal data management and geographic knowledge discovery. A leader in the field, Raju is passionate about understanding the world through (high-) resolution, dimensional, and temporal pixels by developing innovative and computationally efficient algorithms.

Publications

Semantics-enabled framework for spatial image information mining of linked earth observation data

March 27, 2017

Kurte, K. R., Durbha, S. S., King, R. L., Younan, N. H., & Vatsavai, R. (2017). Semantics-enabled framework for spatial image information mining of linked earth observation data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(1), 29-44.

Guest editorial: Big spatial data

October 17, 2016

Vatsavai, R., & Chandola, V. (2016). Guest editorial: Big spatial data. Geoinformatica, 20(4), 797-799.

pFUTURES: A parallel framework for cellular automaton based urban growth models

January 3, 2017

Shashidharan, A., Berkel, D. B., Vatsavai, R. R., & Meentemeyer, R. K. (2016). pFUTURES: A parallel framework for cellular automaton based urban growth models. In Geographic information science, (giscience 2016). (Lecture Notes in Computer Science, 9927) (pp. 163-177).

Monitoring land-cover changes: A machine-learning perspective

January 17, 2017

Karpatne, A., Jiang, Z., Vatsavai, R. R., Shekhar, S., & Kumar, V. (2016). Monitoring land-cover changes: A machine-learning perspective. IEEE Geoscience and Remote Sensing Magazine, 4(2), 8-21.

A scalable probabilistic change detection algorithm for very high resolution (VHR) satellite imagery

January 17, 2017

Hong, S., & Vatsavai, R. R. (2016). A scalable probabilistic change detection algorithm for very high resolution (VHR) satellite imagery. In 2016 ieee international congress on big data - bigdata congress 2016. (IEEE International Congress on Big Data, ) (pp. 275-282).

Multitemporal data mining: From biomass monitoring to nuclear proliferation detection

August 29, 2016

Vatsavai, R. R. (2015). Multitemporal data mining: From biomass monitoring to nuclear proliferation detection. (2015 8th International Workshop on the Analysis of Multitemporal Remote Sensing Images (Multi-Temp), ).

A scalable complex pattern mining framework for global settlement mapping

September 6, 2016

Vatsavai, R. R. (2015). A scalable complex pattern mining framework for global settlement mapping. (2015 IEEE International Congress on Big Data - BigData congress 2015, ) (pp. 514-521).