Does the degree of coarctation of the aorta influence wall shear stress focal heterogeneity? - John Gounley; Rafeed Chaudhury; Madhurima Vardhan; Michael Driscoll; Girish Pathangey; Kevin Winarta; Justin Ryan; David H. Frakes; Amanda Randles (EMBC, 2016)

Numerical simulation of a compound capsule in a constricted microchannel. - John Gounley; Erik W. Draeger; Amanda Randles (ICCS, 2017)

A Computational Framework to Assess the Influence of Changes in Vascular Geometry on Blood Flow. - John Gounley; Madhurima Vardhan; Amanda Randles (PASC, 2017)

Model-based Hyperparameter Optimization of Convolutional Neural Networks for Information Extraction from Cancer Pathology Reports on HPC. - Hong-Jun Yoon; John Gounley; Shang Gao 008; Mohammed M. Alawad; Arvind Ramanathan; Georgia D. Tourassi (BHI, 2019)

Information Extraction from Cancer Pathology Reports with Graph Convolution Networks for Natural Language Texts. - Hong-Jun Yoon; John Gounley; M. Todd Young; Georgia D. Tourassi (IEEE BigData, 2019)

Multi-physics simulations of particle tracking in arterial geometries with a scalable moving window algorithm. - Gregory Herschlag; John Gounley; Sayan Roychowdhury; Erik W. Draeger; Amanda Randles (CLUSTER, 2019)

Immersed Boundary Method Halo Exchange in a Hemodynamics Application. - John Gounley; Erik W. Draeger; Amanda Randles (ICCS (1), 2019)

Investigating the Role of VR in a Simulation-Based Medical Planning System for Coronary Interventions. - Madhurima Vardhan; Harvey Shi; John Gounley; S. James Chen; Andrew Kahn; Jane A. Leopold; Amanda Randles (MICCAI (5), 2019)

Moment representation in the lattice Boltzmann method on massively parallel hardware. - Madhurima Vardhan; John Gounley; Luiz Hegele; Erik W. Draeger; Amanda Randles (SC, 2019)

A framework for comparing vascular hemodynamics at different points in time. - John Gounley; Madhurima Vardhan; Amanda Randles (Comput. Phys. Commun., 2019)

Performance portability study for massively parallel computational fluid dynamics application on scalable heterogeneous architectures. - Seyong Lee; John Gounley; Amanda Randles; Jeffrey S. Vetter (J. Parallel Distributed Comput., 2019)

Evaluating the Influence of Hemorheological Parameters on Circulating Tumor Cell Trajectory and Simulation Time. - Sayan Roychowdhury; John Gounley; Amanda Randles (PASC, 2020)

Accelerated training of bootstrap aggregation-based deep information extraction systems from cancer pathology reports. - Hong-Jun Yoon; Hilda B. Klasky; John P. Gounley; Mohammed M. Alawad; Shang Gao 008; Eric B. Durbin; Xiao-Cheng Wu; Antoinette Stroup; Jennifer A. Doherty; Linda Coyle; Lynne Penberthy; James Blair Christian; et al. (J. Biomed. Informatics, 2020)

Multi-GPU immersed boundary method hemodynamics simulations. - Jeff Ames; Daniel F. Puleri; Peter Balogh; John Gounley; Erik W. Draeger; Amanda Randles (J. Comput. Sci., 2020)

How Distinct Structural Flexibility within SARS-CoV-2 Spike Protein Reveals Potential Therapeutic Targets. - Serena H. Chen; M. Todd Young; John Gounley; Christopher B. Stanley; Debsindhu Bhowmik (IEEE BigData, 2021)

Limitations of Transformers on Clinical Text Classification. - Shang Gao 008; Mohammed M. Alawad; M. Todd Young; John Gounley; Noah Schaefferkoetter; Hong-Jun Yoon; Xiao-Cheng Wu; Eric B. Durbin; Jennifer A. Doherty; Antoinette Stroup; Linda Coyle; Georgia D. Tourassi (IEEE J. Biomed. Health Informatics, 2021)

High Performance Adaptive Physics Refinement to Enable Large-Scale Tracking of Cancer Cell Trajectory. - Daniel F. Puleri; Sayan Roychowdhury; Peter Balogh; John Gounley; Erik W. Draeger; Jeff Ames; Adebayo Adebiyi; Simbarashe Chidyagwai; Benjamín Hernández; Seyong Lee; Shirley V. Moore; Jeffrey S. Vetter; et al. (CLUSTER, 2022)

Computational Workflow for Accelerated Molecular Design Using Quantum Chemical Simulations and Deep Learning Models. - Andrew E. Blanchard; Pei Zhang; Debsindhu Bhowmik; Kshitij Mehta; John Gounley; Samuel Temple Reeve; Stephan Irle; Massimiliano Lupo Pasini (SMC, 2022)

Language models for the prediction of SARS-CoV-2 inhibitors. - Andrew E. Blanchard; John Gounley; Debsindhu Bhowmik; Mayanka Chandra Shekar; Isaac Lyngaas; Shang Gao 008; Junqi Yin; Aristeidis Tsaris; Feiyi Wang; Jens Glaser (Int. J. High Perform. Comput. Appl., 2022)

Automating Genetic Algorithm Mutations for Molecules Using a Masked Language Model. - Andrew E. Blanchard; Mayanka Chandra Shekar; Shang Gao 008; John Gounley; Isaac Lyngaas; Jens Glaser; Debsindhu Bhowmik (IEEE Trans. Evol. Comput., 2022)

Propagation Pattern for Moment Representation of the Lattice Boltzmann Method. - John Gounley; Madhurima Vardhan; Erik W. Draeger; Pedro Valero-Lara; Shirley V. Moore; Amanda Randles (IEEE Trans. Parallel Distributed Syst., 2022)

Characterizing Quantum Classifier Utility in Natural Language Processing Workflows. - Kathleen E. Hamilton; Mayanka Chandra Shekar; John Gounley; Dhanvi Bharadwaj; Prasanna Date; Eduardo Antonio Coello Pérez; In-Saeng Suh; Georgia D. Tourassi (QCE, 2023)

Performance Evaluation of Heterogeneous GPU Programming Frameworks for Hemodynamic Simulations. - Aristotle X. Martin; Geng Liu; William Ladd; Seyong Lee; John Gounley; Jeffrey S. Vetter; Saumil Patel; Silvio Rizzi 001; Victor A. Mateevitsi; Joseph A. Insley; Amanda Randles (SC Workshops, 2023)

Enhancing Adaptive Physics Refinement Simulations Through the Addition of Realistic Red Blood Cell Counts. - Sayan Roychowdhury; Samreen T. Mahmud; Aristotle X. Martin; Peter Balogh; Daniel F. Puleri; John Gounley; Erik W. Draeger; Amanda Randles (SC, 2023)

Moment Representation of Regularized Lattice Boltzmann Methods on NVIDIA and AMD GPUs. - Pedro Valero-Lara; Jeffrey S. Vetter; John Gounley; Amanda Randles (SC Workshops, 2023)

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. - Shuaiwen Leon Song; Bonnie Kruft; Minjia Zhang; Conglong Li; Shiyang Chen 004; Chengming Zhang 006; Masahiro Tanaka; Xiaoxia Wu; Jeff Rasley; Ammar Ahmad Awan; Connor Holmes; Martin Cai; et al. (CoRR, 2023)

Ultra-Long Sequence Distributed Transformer. - Xiao Wang 004; Isaac Lyngaas; Aristeidis Tsaris; Peng Chen 035; Sajal Dash; Mayanka Chandra Shekar; Tao Luo 014; Hong-Jun Yoon; Mohamed Wahib; John Gounley (CoRR, 2023)

Effect of constitutive law on the erythrocyte membrane response to large strains. - Marianna Pepona; John Gounley; Amanda Randles (Comput. Math. Appl., 2023)

FrESCO: Framework for Exploring Scalable Computational Oncology. - Adam Spannaus; John Gounley; Mayanka Chandra Shekar; Zachary R. Fox; Jamaludin Mohd-Yusof; Noah Schaefferkoetter; Heidi A. Hanson (J. Open Source Softw., 2023)

TwoFold: Highly accurate structure and affinity prediction for protein-ligand complexes from sequences. - Darren J. Hsu; Hao Lu 001; Aditya Kashi; Michael A. Matheson; John Gounley; Feiyi Wang; Wayne Joubert; Jens Glaser (Int. J. High Perform. Comput. Appl., 2023)

Adaptive language model training for molecular design. - Andrew E. Blanchard; Debsindhu Bhowmik; Zachary R. Fox; John Gounley; Jens Glaser; Belinda S. Akpa; Stephan Irle (J. Cheminformatics, 2023)

Transferring a Molecular Foundation Model for Polymer Property Predictions. - Pei Zhang; Logan T. Kearney; Debsindhu Bhowmik; Zachary R. Fox; Amit K. Naskar; John Gounley (J. Chem. Inf. Model., 2023)

Evaluation of pre-training large language models on leadership-class supercomputers. - Junqi Yin; Sajal Dash; John Gounley; Feiyi Wang; Georgia D. Tourassi (J. Supercomput., 2023)

Adiabatic Quantum Support Vector Machines. - Prasanna Date; Dong Jun Woun; Kathleen E. Hamilton; Eduardo Antonio Coello Pérez; Mayanka Chandra Shekar; Francisco Rios; John Gounley; In-Saeng Suh; Travis S. Humble; Georgia D. Tourassi (CoRR, 2024)

MATEY: multiscale adaptive foundation models for spatiotemporal physical systems. - Pei Zhang; M. Paul Laiu; Matthew Norman; Doug Stefanski; John Gounley (CoRR, 2024)

Enhancing molecular design efficiency: Uniting language models and generative networks with genetic algorithms. - Debsindhu Bhowmik; Pei Zhang; Zachary R. Fox; Stephan Irle; John Gounley (Patterns, 2024)

Data Assimilation for Robust UQ Within Agent-Based Simulation on HPC Systems. - Adam Spannaus; Sifat Afroj Moon; John Gounley; Heidi A. Hanson (PASC, 2025)

CAFE AU LAIT: Compute-Aware Federated Augmented Low-Rank AI Training. - Jiayi Wang; John Gounley; Heidi A. Hanson (PASC, 2025)

Global explainability of a deep abstaining classifier. - Sayera Dhaubhadel; Jamaludin Mohd-Yusof; Benjamin H. McMahon; Trilce Estrada; Kumkum Ganguly; Adam Spannaus; John P. Gounley; Xiao-Cheng Wu; Eric B. Durbin; Heidi A. Hanson; Tanmoy Bhattacharya 001 (CoRR, 2025)

A Perspective on Data and Privacy for AI in Healthcare [Industrial and Governmental Activities]. - John Gounley; Heidi A. Hanson (IEEE Comput. Intell. Mag., 2025)

Learning to Diagnose Privately: DP-Powered LLMs for Radiology Report Classification. - Payel Bhattacharjee; Fengwei Tian; Ravi Tandon; Joseph Y. Lo; Heidi A. Hanson; Geoffrey Rubin; Nirav Merchant; John Gounley (CoRR, 2025)

Adiabatic quantum support vector machines. - Prasanna Date; Dong Jun Woun; Kathleen E. Hamilton; Eduardo Antonio Coello Pérez; Mayanka Chandrashekar; Francisco Rios; John Gounley; In-Saeng Suh; Travis S. Humble; Georgia D. Tourassi (Quantum Mach. Intell., 2025)

Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit. - Junqi Yin; Mijanur Palash; M. Paul Laiu; Muralikrishnan Gopalakrishnan Meena; John Gounley; Stephen M. de Bruyn Kops; Feiyi Wang; Ramanan Sankaran; Pei Zhang (CoRR, 2025)