John P Gounley Computational Scientist Contact 865.341.0360 | GOUNLEYJP@ORNL.GOV All Publications Large-scale deep learning for metastasis detection in pathology reports Evaluating algorithmic bias on biomarker classification of breast cancer pathology reports Data Assimilation for Robust UQ Within Agent-Based Simulation on HPC Systems CAFE AU LAIT: Compute-Aware Federated Augmented Low-Rank AI Training A Perspective on Data and Privacy for AI in Healthcare [Industrial and Governmental Activities]... RISKS ASSOCIATED WITH SHARING THE MOSSAIC APIS... Adiabatic Quantum Support Vector Machines MATEY: multiscale adaptive foundation models for spatiotemporal physical systems Enhancing molecular design efficiency: Uniting language models and generative networks with genetic algorithms Path-BigBird: An AI-Driven Transformer Approach to Classification of Cancer Pathology Reports Transferring a Molecular Foundation Model for Polymer Property Predictions Moment Representation of Regularized Lattice Boltzmann Methods on NVIDIA and AMD GPUs Performance Evaluation of Heterogeneous GPU Programming Frameworks for Hemodynamic Simulations Enhancing Adaptive Physics Refinement Simulations Through the Addition of Realistic Red Blood Cell Counts TwoFold: Highly accurate structure and affinity prediction for protein-ligand complexes from sequences... FrESCO: Framework for Exploring Scalable Computational Oncology Characterizing Quantum Classifier Utility in Natural Language Processing Workflows Adaptive language model training for molecular design... Evaluation of pre-training large language models on leadership-class supercomputers Effect of constitutive law on the erythrocyte membrane response to large strains Computational Workflow for Accelerated Molecular Design Using Quantum Chemical Simulations and Deep Learning Models Evaluation of intracoronary hemodynamics identifies perturbations in vorticity Language Models for the Prediction of SARS-CoV-2 Inhibitors High Performance Adaptive Physics Refinement to Enable Large-Scale Tracking of Cancer Cell Trajectory IMPLEMENTATION OF THE ENERGY EQUATION SOLVER TO THE LATTICE BOLTZMANN METHOD-BASED CODE PRATHAM Pagination Current page 1 Page 2 Next page ›› Last page Last » Key Links Curriculum Vitae Google Scholar ORCID Organizations Computing and Computational Sciences Directorate Computational Sciences and Engineering Division Advanced Computing in Health Sciences Section Scalable Biomedical Modeling Group
Research Highlight Monte Carlo Methods in Predicting Cell Survival in Digital Twin Radiotherapy Simulations
Research Highlight Effect of Constitutive Law on the Response of the Erythrocyte Membrane to Large Strains
Research Highlight High Performance Adaptive Physics Refinement to Enable Large-Scale Tracking of Cancer Cell Trajectory