Dr. Harini Sridharan
Post-Doctoral Research Associate
PhD, Geospatial Science, University of Texas at Dallas (2012)
Master of Science, Geospatial Science, University of Texas at Dallas (2009)
Bachelor of Engineering, Geo-Informatics, College of Engineering, Anna University (2007)
Research Experience and Interests
Dr. Sridharan joined the Geographic Information Science and Technology group at ORNL in 2012 as postdoctoral research associate. Her current research interests include developing prototypes for object recognition from LiDAR and hyperspatial/hyperspectral optical imagery, identifying semantic information from remote sensing data and designing GPU based processing systems to handle the complexities of large volume remote sensing data.
Her doctoral dissertation at the University of Texas at Dallas involved developing a novel object-based classifier for classifying hyperspatial-hyperspectral data. Dr. Sridharan received her master’s degree in Geospatial Science in May 2009 from the University of Texas at Dallas. Her research work for her master’s degree focused on developing spatial autocorrelation based regression models and spatial disaggregation models for population estimation and areal interpolations using LiDAR derived building volume information. During her graduate study, Dr. Sridharan has won several awards and recognition. DigitalGlobe recognized her work on urban forest mapping using WorldView-2 data as one of the top fifteen studies worldwide and awarded her at the 2011 Geospatial World Forum meeting. She also received an ASPRS scholarship in 2011 and was invited by ERDAS Imagine to work as an intern during Summer 2011. At the 2011 annual meeting of Association of American Geographers (AAG), she was awarded the Second Place for the Students Illustrated Paper Competition by the Remote Sensing Speciality Group. She has extensive teaching and working experience in several areas of geospatial science including active and passive remote sensing, spatial statistics, GIS database systems and spatial analysis & modeling.