Bio
John Gounley is a computational scientist in the Computational Sciences and Engineering Division at Oak Ridge National Laboratory, where he leads the Scalable Biomedical Modeling group.
Prior to joining ORNL, John held postdoctoral positions in Laboratoire M2P2 at Ecole Centrale Marseille and in the Department of Biomedical Engineering at Duke University. While at Duke, he had postdoctoral fellowships with the Hartwell Foundation and with the Big Data-Scientist Training Enhancement Program (BD-STEP) of the National Cancer Institute (NCI) and the Veterans Health Administration. John received his PhD in Computational & Applied Mathematics at Old Dominion University.
John’s research focuses on scalability of algorithms for biomedical simulations and data. He contributes to MOSSAIC, a collaboration with the NCI to develop deep learning models for cancer surveillance, and EHRLICH, a DOE Biopreparedness Research Virtual Environment (BRaVE) project to integrate heterogeneous data streams and agent-based modeling to facilitate data-driven, real-time simulation of biothreat scenarios. His research interests also include language models, distributed deep learning, and lattice Boltzmann methods.