Accelerating Data Acquisition, Reduction, and Analysis at the Spallation Neutron Source. - Galen M. Shipman; Stuart I. Campbell; David Dillow; Mathieu Doucet; Jim Kohl; Garrett E. Granroth; Ross G. Miller; Dale Stansberry; Thomas Proffen; Russel Taylor (eScience, 2014)

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)

Understanding Perspectives on Sharing Neutron Data at Oak Ridge National Laboratory. - Devan Ray Donaldson; Shawn Martin; Thomas Proffen (Data Sci. J., 2017)

PANORAMA: An approach to performance modeling and diagnosis of extreme-scale workflows. - Ewa Deelman; Christopher D. Carothers; Anirban Mandal; Brian Tierney; Jeffrey S. Vetter; Ilya Baldin; Claris Castillo; Gideon Juve; Dariusz Król 002; Vickie E. Lynch; Benjamin Mayer; Jeremy S. Meredith; et al. (Int. J. High Perform. Comput. Appl., 2017)

An automated analysis workflow for optimization of force-field parameters using neutron scattering data. - Vickie E. Lynch; Jose M. Borreguero; Debsindhu Bhowmik; Panchapakesan Ganesh; Bobby G. Sumpter; Thomas Proffen; Monojoy Goswami (J. Comput. Phys., 2017)

Learning to Predict Material Structure from Neutron Scattering Data. - Cristina Garcia-Cardona; Ramakrishnan Kannan; Travis Johnston; Thomas Proffen; Katharine Page; Sudip K. Seal (IEEE BigData, 2019)

Structure Prediction from Neutron Scattering Profiles: A Data Sciences Approach. - Cristina Garcia-Cardona; Ramakrishnan Kannan; Travis Johnston; Thomas Proffen; Sudip K. Seal (IEEE BigData, 2020)

Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing. - Pravallika Devineni; Panchapakesan Ganesh; Nikhil Sivadas; Abhijeet Dhakane; Ketan Maheshwari; Drahomira Herrmannova; Ramakrishnan Kannan; Seung-Hwan Lim; Thomas E. Potok; Jordan B. Chipka; Priyantha Mudalige; Mark Coletti; et al. (SMC, 2021)

Co-design Center for Exascale Machine Learning Technologies (ExaLearn). - Francis J. Alexander; James A. Ang; Jenna A. Bilbrey; Jan Balewski; Tiernan Casey; Ryan Chard; Jong Choi 001; Sutanay Choudhury; Bert J. Debusschere; Anthony M. DeGennaro; Nikoli Dryden; J. Austin Ellis; et al. (Int. J. High Perform. Comput. Appl., 2021)

Machine learning for neutron scattering at ORNL. - Mathieu Doucet; Anjana M. Samarakoon; Changwoo Do; William T. Heller; Richard Archibald; D. Alan Tennant; Thomas Proffen; Garrett E. Granroth (Mach. Learn. Sci. Technol., 2021)

A Parallel Machine Learning Workflow for Neutron Scattering Data Analysis. - Tianle Wang 001; Sudip K. Seal; Ramakrishnan Kannan; Cristina Garcia-Cardona; Thomas Proffen; Shantenu Jha (IPDPS Workshops, 2023)

An Active Learning-Based Streaming Pipeline for Reduced Data Training of Structure Finding Models in Neutron Diffractometry. - Tianle Wang 001; Jorge Ramirez; Cristina Garcia-Cardona; Thomas Proffen; Shantenu Jha; Sudip K. Seal (IEEE Big Data, 2024)