Jacob Hinkle

Jacob Hinkle is a research scientist in the Advanced Computing for Health Sciences Section, part of the Computational Sciences and Engineering Division at Oak Ridge National Laboratory (ORNL). He holds B.S. degrees in Physics and Mathematics from Miami University and a Ph.D. in Bioengineering from the University of Utah. His Ph.D. work focused on statistical modeling of shape change using Riemannian geometry with applications in medical imaging. Prior to joining ORNL, he worked as a research scientist at the National Renewable Energy Laboratory, applying mathematical land statistical methods to biological imaging and data analysis problems.

At ORNL, Dr. Hinkle has led research efforts on scalable deep learning and advanced image analysis as part of the ORNL Artificial Intelligence (AI) Initiative. Additionally, he has developed Bayesian deep learning methods including linking deep neural networks and deep Gaussian processes. His research interests include novel approaches to mathematical modeling and Bayesian data analysis particularly using large-scale HPC, and he is involved with imaging applications in geospatial intelligence, materials science, bioscience, and neuroscience.