Dr. Souparno Ghosh, Ph.D
Souparno is a Big Data and Machine Learning expert having developed statistical models for spatial interpolation, population demographics, population density estimation, animal tracking, drug response prediction and uncertainty quantification. His major interest lies in developing multi-level, multi-scale models for spatial data and integration of deterministic models in stochastic setup to improve prediction performance. His current projects include development of machine learning techniques for functional data, adaptation of random forests for spatial/spatio-temporal processes, and generating model based spatial risk maps for disaster events.
Souparno is an assistant professor in the Department of Mathematics and Statistics at Texas Tech University. He received his Ph.D. in Statistics from Texas A&M University and was a postdoctoral associate at Duke University for several years.
Expertise: Machine Learning, Big Data Modeling