Chris Tennant

According to our database, Chris Tennant authored at least 16 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Toward a Fully Autonomous, AI-Native Particle Accelerator.

Chris Tennant

CoRR, February, 2026

Explainable Graph Learning for Particle Accelerator Operations.

Song Wang, Chris Tennant, Jundong Li

Trans. Mach. Learn. Res., 2026

2025

From Natural Language to Control Signals: A Conceptual Framework for Semantic Channel Finding in Complex Experimental Infrastructure.

Thorsten Hellert, Nikolay Agladze, Alex Giovannone, Jan Jug, Frank Mayet, Mark Sherwin, Antonin Sulc, Chris Tennant

CoRR, December, 2025

A Core Ontology for Particle Accelerators: Interoperable Data and Workflows Across Facilities.

Chris Tennant

CoRR, December, 2025

eLog analysis for accelerators: status and future outlook.

Antonin Sulc, Thorsten Hellert, Aaron Zachary Reed, Adam Carpenter, Alex Bien, Chris Tennant, Claudio Bisegni, Daniel Lersch, Daniel Ratner, David Lawrence, Diana McSpadden, Hayden Hoschouer, Jason St. John, Thomas Britton

CoRR, June, 2025

2024

Accelerating cavity fault prediction using deep learning at Jefferson Laboratory.

Md Monibor Rahman, Adam Carpenter, Khan M. Iftekharuddin, Chris Tennant

Mach. Learn. Sci. Technol., 2024

Graph learning for particle accelerator operations.

Song Wang, Chris Tennant, Daniel Moser, Theo Larrieu, Jundong Li

Frontiers Big Data, 2024

Data-Driven Gradient Optimization for Field Emission Management in a Superconducting Radio-Frequency Linac.

Steven Goldenberg, Kawser Ahammed, Adam Carpenter, Jiang Li, Riad Suleiman, Chris Tennant

CoRR, 2024

2023

A smart alarm for particle accelerator beamline operations.

Chris Tennant, Brian Freeman, Reza Kazimi, Daniel Moser, Dan T. Abell, Jonathan P. Edelen, Joshua Einstein-Curtis

Mach. Learn. Sci. Technol., March, 2023

Uncertainty Aware Deep Learning for Fault Prediction Using Multivariate Time Series Signals.

Md Monibor Rahman, Lasitha Vidyaratne, Adam Carpenter, Chris Tennant, Khan M. Iftekharuddin

Proceedings of the International Joint Conference on Neural Networks, 2023

2022

Deep Cellular Recurrent Network for Efficient Analysis of Time-Series Data With Spatial Information.

Lasitha Vidyaratne, Mahbubul Alam, Alexander M. Glandon, Anna Shabalina, Chris Tennant, Khan M. Iftekharuddin

IEEE Trans. Neural Networks Learn. Syst., 2022

2021

Deep Learning Based Superconducting Radio-Frequency Cavity Fault Classification at Jefferson Laboratory.

Lasitha Vidyaratne, Adam Carpenter, Tom Powers, Chris Tennant, Khan M. Iftekharuddin, Md Monibor Rahman, Anna Shabalina Solopova

Frontiers Artif. Intell., 2021

2020

Superconducting radio-frequency cavity fault classification using machine learning at Jefferson Laboratory.

Chris Tennant, Adam Carpenter, Tom Powers, Anna Shabalina Solopova, Lasitha Vidyaratne, Khan Iftekharuddin

CoRR, 2020

2018

Resolving the Influence of Forest-Canopy Structure on Snow Depth Distributions with Terrestrial Laser Scanning.

Zach Uhlmann, Nancy F. Glenn, Lucas P. Spaete, Christopher A. Hiemstra, Chris Tennant, Jim McNamara

Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

Nasa Snowex'17 in SITU Measurements and Ground-Based Remote Sensing.

Ludovic Brucker, Christopher A. Hiemstra, Hans-Peter Marshall, Kelly Elder, Roger D. De Roo, Mohammad Mousavi, Francis Bliven, Walt Peterson, Jeffrey Deems, Peter Gadomski, Arthur Gelvin, Lucas P. Spaete, Theodore B. Barnhart, Ty Brandt, John F. Burkhart, Christopher J. Crawford, Tri Datta, Havard Erikstrod, Nancy F. Glenn, Katherine Hale, Brent Holben, Paul R. Houser, Keith Jennings, Richard E. J. Kelly, Jason Kraft, Alexandre Langlois, Daniel McGrath, Chelsea Merriman, Noah P. Molotch, Anne W. Nolin, Chris Polashenski, Mark Raleigh, Karl Rittger, Chago Rodriguez, Alexandre Roy, S. McKenzie Skiles, Eric Small, Marco Tedesco, Chris Tennant, Aaron Thompson, Zach Uhlmann, Ryan Webb, Matt Wingo

Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

2017

A first overview of SnowEx ground-based remote sensing activities during the winter 2016-2017.

Ludovic Brucker, Christopher A. Hiemstra, Hans-Peter Marshall, Kelly Elder, Roger D. De Roo, Mohammad Mousavi, Francis Bliven, Walt Peterson, Jeffrey S. Deems, Peter Gadomski, Arthur Gelvin, Lucas P. Spaete, Theodore B. Barnhart, Ty Brandt, John F. Burkhart, Christopher J. Crawford, Tri Datta, Havard Erikstrod, Nancy F. Glenn, Katherine Hale, Brent Holben, Paul R. Houser, Keith Jennings, Richard E. J. Kelly, Jason Kraft, Alexandre Langlois, Daniel McGrath, Chelsea Merriman, Noah P. Molotch, Anne W. Nolin, Chris Polashenski, Mark Raleigh, Karl Rittger, Chago Rodriguez, Alexandre Roy, S. McKenzie Skiles, Eric Small, Marco Tedesco, Chris Tennant, Aaron Thompson, Liuxi Tian, Zach Uhlmann, Ryan Webb, Matt Wingo

Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017