Thomas Proffen

According to our database, Thomas Proffen authored at least 11 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2023

A Parallel Machine Learning Workflow for Neutron Scattering Data Analysis.

Tianle Wang, Sudip K. Seal, Ramakrishnan Kannan, Cristina Garcia-Cardona, Thomas Proffen, Shantenu Jha

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

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

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, Sutanay Choudhury, Bert J. Debusschere, Anthony M. DeGennaro, Nikoli Dryden, J. Austin Ellis, Ian T. Foster, Cristina Garcia-Cardona, Sayan Ghosh, Peter Harrington, Yunzhi Huang, Shantenu Jha, Travis Johnston, Ai Kagawa, Ramakrishnan Kannan, Neeraj Kumar, Zhengchun Liu, Naoya Maruyama, Satoshi Matsuoka, Erin McCarthy, Jamaludin Mohd-Yusof, Peter Nugent, Yosuke Oyama, Thomas Proffen, David Pugmire, Sivasankaran Rajamanickam, Vinay Ramakrishnaiah, Malachi Schram, Sudip K. Seal, Ganesh Sivaraman, Christine Sweeney, Li Tan, Rajeev Thakur, Brian Van Essen, Logan T. Ward, Paul M. Welch, Michael Wolf, Sotiris S. Xantheas, Kevin G. Yager, Shinjae Yoo, Byung-Jun Yoon

Int. J. High Perform. Comput. Appl., 2021

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, Sajal Dash, Arnab Kumar Paul, Sarp Oral, Feiyi Wang, Bill Kay, Melissa R. Allen-Dumas, Christa Brelsford, Joshua R. New, Andy Berres, Kuldeep R. Kurte, Jibonananda Sanyal, Levi Sweet, Chathika Gunaratne, Maxim A. Ziatdinov, Rama K. Vasudevan, Sergei V. Kalinin, Olivera Kotevska, Jean C. Bilheux, Hassina Z. Bilheux, Garrett E. Granroth, Thomas Proffen, Rick Riedel, Peter F. Peterson, Shruti R. Kulkarni, Kyle P. Kelley, Stephen Jesse, Maryam Parsa

Proceedings of the Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation, 2021

2020

Structure Prediction from Neutron Scattering Profiles: A Data Sciences Approach.

Cristina Garcia-Cardona, Ramakrishnan Kannan, Travis Johnston, Thomas Proffen, Sudip K. Seal

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019

Learning to Predict Material Structure from Neutron Scattering Data.

Cristina Garcia-Cardona, Ramakrishnan Kannan, Travis Johnston, Thomas Proffen, Katharine Page, Sudip K. Seal

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

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

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, Vickie E. Lynch, Benjamin Mayer, Jeremy S. Meredith, Thomas Proffen, Paul Ruth, Rafael Ferreira da Silva

Int. J. High Perform. Comput. Appl., 2017

Understanding Perspectives on Sharing Neutron Data at Oak Ridge National Laboratory.

Devan Ray Donaldson, Shawn Martin, Thomas Proffen

Data Sci. J., 2017

2015

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

Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015

2014

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

Proceedings of the 10th IEEE International Conference on e-Science, 2014