Kishansingh Rajput

According to our database, Kishansingh Rajput authored at least 19 papers between 2021 and 2026.

Collaborative distances:

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

2026

Explainable physics-based constraints on reinforcement learning for accelerator optimization.

Jonathan Colen, Malachi Schram, Kishansingh Rajput, Armen Kasparian

Mach. Learn. Sci. Technol., 2026

2025

Uncertainty Guided Online Ensemble for Non-stationary Data Streams in Fusion Science.

Kishansingh Rajput, Malachi Schram, Brian Sammuli, Sen Lin

CoRR, November, 2025

Harnessing the power of gradient-based simulations for multi-objective optimization in particle accelerators.

Kishansingh Rajput, Malachi Schram, Auralee Edelen, Jonathan Colen, Armen Kasparian, Ryan Roussel, Adam Carpenter, He Zhang, Jay Benesch

Mach. Learn. Sci. Technol., 2025

Outlook towards deployable continual learning for particle accelerators.

Kishansingh Rajput, Sen Lin, Auralee Edelen, Willem Blokland, Malachi Schram

Mach. Learn. Sci. Technol., 2025

Geometric GNNs for charged particle tracking at GlueX.

Ahmed Hossam Mohammed, Kishansingh Rajput, Simon Taylor, Denis Furletov, Sergey Furletov, Malachi Schram

Mach. Learn. Sci. Technol., 2025

SAGIPS: a physics-inspired scalable asynchronous generative inverse-problem solver.

Daniel Lersch, Malachi Schram, Zhenyu Dai, Kishansingh Rajput, Nobuo Sato, Xingfu Wu, J. Taylor Childers, Steven Goldenberg

Mach. Learn. Sci. Technol., 2025

2024

Artificial Intelligence for the Electron Ion Collider (AI4EIC).

C. Allaire, R. Ammendola, E.-C. Aschenauer, M. Balandat, Marco Battaglieri, J. C. Bernauer, M. Bondì, N. Branson, T. Britton, Anja Butter, I. Chahrour, P. Chatagnon, Evaristo Cisbani, E. W. Cline, S. Dash, C. T. Dean, W. Deconinck, A. Deshpande, Markus Diefenthaler, R. Ent, Cristiano Fanelli, M. Finger, E. Fol, S. Furletov, Y. Gao, James Giroux, N. C. Gunawardhana Waduge, Omar Hassan, P. L. Hegde, Roger José Hernández-Pinto, Astrid N. Hiller Blin, Tanja Horn, J. Huang, A. Jalotra, D. Jayakodige, B. Joo, M. Junaid, N. Kalantarians, Piyush Karande, B. Kriesten, R. Kunnawalkam Elayavalli, Y. Li, Meifeng Lin, Frank Liu, S. Liuti, G. Matousek, Matthew McEneaney, Diana McSpadden, T. Menzo, T. Miceli, Vinicius Mikuni, R. Montgomery, Benjamin Nachman, R. R. Nair, J. Niestroy, Salvador A. Ochoa-Oregon, J. Oleniacz, J. D. Osborn, Churamani Paudel, Connor Pecar, C. Peng, Gabriel N. Perdue, W. Phelps, Martin L. Purschke, H. Rajendran, Kishansingh Rajput, Y. Ren, David Francisco Rentería-Estrada, D. Richford, B. J. Roy, D. Roy, A. Saini, Nobuo Sato, T. Satogata, German Sborlini, Malachi Schram, David Shih, J. Singh, R. Singh, Andrzej Siódmok, J. Stevens, P. Stone, L. Suarez, K. Suresh, Abdel Nasser Tawfik, Fernando Torales Acosta, N. Tran, R. Trotta, F. J. Twagirayezu, Richard Tyson, S. Volkova, Anselm Vossen, Eric Walter, Daniel Whiteson, Michael Williams, S. Wu, N. Zachariou, P. Zurita

Comput. Softw. Big Sci., December, 2024

Robust errant beam prognostics with conditional modeling for particle accelerators.

Kishansingh Rajput, Malachi Schram, Willem Blokland, Yasir Alanazi, Pradeep Ramuhalli, Alexander Zhukov, Charles Peters, Ricardo Vilalta

Mach. Learn. Sci. Technol., March, 2024

Distance preserving machine learning for uncertainty aware accelerator capacitance predictions.

Steven Goldenberg, Malachi Schram, Kishansingh Rajput, Thomas Britton, Chris Pappas, Dan Lu, Jared Walden, Majdi I. Radaideh, Sarah Cousineau, Sudarshan Harave

Mach. Learn. Sci. Technol., 2024

SAGIPS: A Scalable Asynchronous Generative Inverse Problem Solver.

Daniel Lersch, Malachi Schram, Zhenyu Dai, Kishansingh Rajput, Xingfu Wu, N. Sato, J. Taylor Childers

CoRR, 2024

Hydra: Computer Vision for Data Quality Monitoring.

Thomas Britton, Torri Jeske, David Lawrence, Kishansingh Rajput

CoRR, 2024

Evaluating DTW Measures via a Synthesis Framework for Time-Series Data.

Kishansingh Rajput, Duong Binh Nguyen, Guoning Chen

CoRR, 2024

2023

Uncertainty Aware Deep Learning for Particle Accelerators.

Kishansingh Rajput, Malachi Schram, Karthik Somayaji N. S.

CoRR, 2023

Artificial Intelligence for the Electron Ion Collider (AI4EIC).

C. Allaire, R. Ammendola, E.-C. Aschenauer, M. Balandat, Marco Battaglieri, J. C. Bernauer, M. Bondì, N. Branson, Thomas Britton, Anja Butter, I. Chahrour, P. Chatagnon, Evaristo Cisbani, E. W. Cline, S. Dash, C. T. Dean, W. Deconinck, A. Deshpande, Markus Diefenthaler, R. Ent, Cristiano Fanelli, M. Finger, M. Finger Jr., E. Fol, S. Furletov, Yuan Gao, James Giroux, N. C. Gunawardhana Waduge, R. Harish, Omar Hassan, P. L. Hegde, Roger José Hernández-Pinto, Astrid N. Hiller Blin, Tanja Horn, J. Huang, D. Jayakodige, B. Joo, M. Junaid, Piyush Karande, B. Kriesten, R. Kunnawalkam Elayavalli, M. Lin, Frank Liu, S. Liuti, G. Matousek, Matthew McEneaney, Diana McSpadden, T. Menzo, T. Miceli, Vinicius Mikuni, R. Montgomery, Benjamin Nachman, R. R. Nair, J. Niestroy, Salvador A. Ochoa-Oregon, J. Oleniacz, J. D. Osborn, Churamani Paudel, Connor Pecar, C. Peng, Gabriel N. Perdue, W. Phelps, Martin L. Purschke, Kishansingh Rajput, Y. Ren, David Francisco Rentería-Estrada, D. Richford, B. J. Roy, D. Roy, Nobuo Sato, T. Satogata, German Sborlini, Malachi Schram, David Shih, J. Singh, R. Singh, Andrzej Siódmok, P. Stone, J. Stevens, L. Suarez, K. Suresh, Abdel Nasser Tawfik, Fernando Torales Acosta, N. Tran, R. Trotta, F. J. Twagirayezu, Richard Tyson, S. Volkova, Anselm Vossen, Eric Walter, Daniel Whiteson, Michael Williams, S. Wu, N. Zachariou, P. Zurita

CoRR, 2023

Multi-module based CVAE to predict HVCM faults in the SNS accelerator.

Yasir Alanazi, Malachi Schram, Kishansingh Rajput, Steven Goldenberg, Lasitha Vidyaratne, Chris Pappas, Majdi I. Radaideh, Dan Lu, Pradeep Ramuhalli, Sarah Cousineau

CoRR, 2023

2022

Time series anomaly detection in power electronics signals with recurrent and ConvLSTM autoencoders.

Majdi I. Radaideh, Chris Pappas, Jared Walden, Dan Lu, Lasitha Vidyaratne, Thomas Britton, Kishansingh Rajput, Malachi Schram, Sarah Cousineau

Digit. Signal Process., 2022

Probabilistic Envelope based Visualization for Monitoring Drilling Well Data Logging.

Kishansingh Rajput, Guoning Chen

Proceedings of the 17th International Joint Conference on Computer Vision, 2022

2021

Uncertainty aware anomaly detection to predict errant beam pulses in the SNS accelerator.

Willem Blokland, Pradeep Ramuhalli, Charles Peters, Yigit A. Yucesan, Alexander Zhukov, Malachi Schram, Kishansingh Rajput, Torri Jeske

CoRR, 2021

AI Enabled Data Quality Monitoring with Hydra.

Thomas Britton, David Lawrence, Kishansingh Rajput

CoRR, 2021