Visualization of Cardiac Bioelectricty - A Case Study. - Robert S. MacLeod; N. E. Harrison; Christopher R. Johnson 001; Michael A. Matheson (IEEE Visualization, 1992)

Visualization blackboard-visualizing bioelectric fields. - Robert S. MacLeod; Christopher R. Johnson 001; Michael A. Matheson (IEEE Computer Graphics and Applications, 1993)

Computational Medicine: Bioelectric Field Problems. - Christopher R. Johnson 001; Robert S. MacLeod; Michael A. Matheson (Computer, 1993)

Shock wave / turbulent boundary layer interactions. - Michael A. Matheson; Allan D. Grosvenor; Alexander A. Zheltovodov (SC Companion, 2011)

Immersive visualization for materials science data analysis using the Oculus Rift. - Margaret Drouhard; Chad A. Steed; Steven E. Hahn; Thomas Proffen; Jamison Daniel; Michael A. Matheson (IEEE BigData, 2015)

Kernels for scalable data analysis in science: Towards an architecture-portable future. - Sreenivas R. Sukumar 001; Ramakrishnan Kannan; Seung-Hwan Lim; Michael A. Matheson (IEEE BigData, 2016)

Mini-apps for high performance data analysis. - Sreenivas R. Sukumar 001; Michael A. Matheson; Ramakrishnan Kannan; Seung-Hwan Lim (IEEE BigData, 2016)

Big data analytics on HPC architectures: Performance and cost. - Peter Xenopoulos; Jamison Daniel; Michael A. Matheson; Sreenivas R. Sukumar 001 (IEEE BigData, 2016)

Programming with BIG Data in R: Scaling Analytics from One to Thousands of Nodes. - Drew Schmidt; Wei-Chen Chen; Michael A. Matheson; George Ostrouchov (Big Data Res., 2017)

Exascale deep learning for climate analytics. - Thorsten Kurth; Sean Treichler; Joshua Romero; Mayur Mudigonda; Nathan Luehr; Everett H. Phillips; Ankur Mahesh; Michael A. Matheson; Jack Deslippe; Massimiliano Fatica; Prabhat; Michael Houston (SC, 2018)

Defining Big Data Analytics Benchmarks for Next Generation Supercomputers. - Drew Schmidt; Junqi Yin; Michael A. Matheson; Bronson Messer; Mallikarjun Shankar (CoRR, 2018)

PLANC: Parallel Low Rank Approximation with Non-negativity Constraints. - Srinivas Eswar; Koby Hayashi; Grey Ballard; Ramakrishnan Kannan; Michael A. Matheson; Haesun Park (CoRR, 2019)

Exascale Deep Learning for Scientific Inverse Problems. - Nouamane Laanait; Joshua Romero; Junqi Yin; M. Todd Young; Sean Treichler; Vitalii Starchenko; Albina Y. Borisevich; Alex Sergeev; Michael A. Matheson (CoRR, 2019)

Towards the Development of Entropy-Based Anomaly Detection in an Astrophysics Simulation. - Drew Schmidt; Bronson Messer; M. Todd Young; Michael A. Matheson (CoRR, 2020)

PLANC: Parallel Low-rank Approximation with Nonnegativity Constraints. - Srinivas Eswar; Koby Hayashi; Grey Ballard; Ramakrishnan Kannan; Michael A. Matheson; Haesun Park (ACM Trans. Math. Softw., 2021)

Accelerating Collective Communication in Data Parallel Training across Deep Learning Frameworks. - Joshua Romero; Junqi Yin; Nouamane Laanait; Bing Xie; M. Todd Young; Sean Treichler; Vitalii Starchenko; Albina Y. Borisevich; Alex Sergeev; Michael A. Matheson (NSDI, 2022)

Climbing the Summit and Pushing the Frontier of Mixed Precision Benchmarks at Extreme Scale. - Hao Lu 001; Michael A. Matheson; Vladyslav Oles; J. Austin Ellis; Wayne Joubert; Feiyi Wang (SC, 2022)

Optimizing Communication in 2D Grid-Based MPI Applications at Exascale. - Hao Lu 001; Piyush Sao; Michael A. Matheson; Ramakrishnan Kannan; Feiyi Wang; Thomas E. Potok (EuroMPI, 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)

Mixed-precision numerics in scientific applications: survey and perspectives. - Aditya Kashi; Hao Lu; Wesley Brewer; David Rogers; Michael A. Matheson; Mallikarjun Shankar; Feiyi Wang (CoRR, 2024)

Scaling the memory wall using mixed-precision - HPG-MxP on an exascale machine. - Aditya Kashi; Nicholson Koukpaizan; Hao Lu 001; Michael A. Matheson; Sarp Oral; Feiyi Wang (CoRR, 2025)