Egemen Kolemen

According to our database, Egemen Kolemen authored at least 25 papers between 2019 and 2026.

Collaborative distances:

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

2026

Offline Reinforcement Learning for Rotation Profile Control in Tokamaks.

Rohit Sonker, Hiro Josep Farre Kaga, Jiayu Chen, Andrew Rothstein, Ian Char, Ricardo Shousha, Egemen Kolemen, Jeff G. Schneider

CoRR, May, 2026

TokEye: Fast Signal Extraction for Fluctuating Time Series via Offline Self-Supervised Learning From Fusion Diagnostics to Bioacoustics.

Nathaniel Chen, Kouroche Bouchiat, Peter Steiner, Andrew Rothstein, David R. Smith, Max Austin, Michael Van Zeeland, Azarakhsh Jalalvand, Egemen Kolemen

CoRR, February, 2026

Beyond the Loss Curve: Scaling Laws, Active Learning, and the Limits of Learning from Exact Posteriors.

Arian Khorasani, Nathaniel Chen, Yug D. Oswal, Akshat Santhana Gopalan, Egemen Kolemen, Ravid Shwartz-Ziv

CoRR, February, 2026

Multimodal Super-Resolution: Discovering Hidden Physics and Its Application to Fusion Plasmas (Abstract Reprint).

Azarakhsh Jalalvand, SangKyeun Kim, Jaemin Seo, Qiming Hu, Max Curie, Peter Steiner, Andrew Oakleigh Nelson, Yong-Su Na, Egemen Kolemen

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Enabling Integrated AI Control on DIII-D: A Control System Design with State-of-the-art Experiments.

Andrew Rothstein, Hiro Josep Farre Kaga, Jalal Butt, Ricardo Shousha, Keith Erickson, Takuma Wakatsuki, Azarakhsh Jalalvand, Peter Steiner, SangKyeun Kim, Egemen Kolemen

CoRR, November, 2025

PCGBandit: One-shot acceleration of transient PDE solvers via online-learned preconditioners.

Mikhail Khodak, Min Ki Jung, Brian Wynne, Edmond Chow, Egemen Kolemen

CoRR, September, 2025

Regulation Compliant AI for Fusion: Real-Time Image Analysis-Based Control of Divertor Detachment in Tokamaks.

Nathaniel Chen, Cheolsik Byun, Azarakhsh Jalalvand, SangKyeun Kim, Andrew Rothstein, Filippo Scotti, Steve Allen, David Eldon, Keith Erickson, Egemen Kolemen

CoRR, July, 2025

ZERNIPAX: A fast and accurate Zernike polynomial calculator in Python.

Yigit Gunsur Elmacioglu, Rory Conlin, Daniel W. Dudt, Dario Panici, Egemen Kolemen

Appl. Math. Comput., 2025

Multi-Timescale Dynamics Model Bayesian Optimization for Plasma Stabilization in Tokamaks.

Rohit Sonker, Alexandre Capone, Andrew Rothstein, Hiro Josep Farre Kaga, Egemen Kolemen, Jeff Schneider

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Avoiding fusion plasma tearing instability with deep reinforcement learning.

Jaemin Seo, SangKyeun Kim, Azarakhsh Jalalvand, Rory Conlin, Andrew Rothstein, Joseph Abbate, Keith Erickson, Josiah Wai, Ricardo Shousha, Egemen Kolemen

Nat., 2024

Real-time confinement regime detection in fusion plasmas with convolutional neural networks and high-bandwidth edge fluctuation measurements.

Kevin Gill, David R. Smith, Semin Joung, Benedikt Geiger, George McKee, J. Zimmerman, Ryan N. Coffee, Azarakhsh Jalalvand, Egemen Kolemen

Mach. Learn. Sci. Technol., 2024

Model-free stabilization via Extremum Seeking using a cost neural estimator.

Sara Dubbioso, Azarakhsh Jalalvand, Josiah Wai, Gianmaria De Tommasi, Egemen Kolemen

Expert Syst. Appl., 2024

High Order Free Boundary MHD Equilibria in DESC.

Rory Conlin, Jonathan Schilling, Daniel W. Dudt, Dario Panici, Rogerio Jorge, Egemen Kolemen

CoRR, 2024

Diag2Diag: Multimodal super-resolution diagnostics for physics discovery with application to fusion.

Azarakhsh Jalalvand, Max Curie, SangKyeun Kim, Peter Steiner, Jaemin Seo, Qiming Hu, Andrew Oakleigh Nelson, Egemen Kolemen

CoRR, 2024

Full Shot Predictions for the DIII-D Tokamak via Deep Recurrent Networks.

Ian Char, Youngseog Chung, Joseph Abbate, Egemen Kolemen, Jeff G. Schneider

CoRR, 2024

Stellarator Optimization with Constraints.

Rory Conlin, Patrick Kim, Daniel W. Dudt, Dario Panici, Egemen Kolemen

CoRR, 2024

2023

Offline Model-Based Reinforcement Learning for Tokamak Control.

Ian Char, Joseph Abbate, Laszlo Bardoczi, Mark D. Boyer, Youngseog Chung, Rory Conlin, Keith Erickson, Viraj Mehta, Nathan Richner, Egemen Kolemen, Jeff G. Schneider

Proceedings of the Learning for Dynamics and Control Conference, 2023

Multimodal Prediction of Tearing Instabilities in a Tokamak.

Jaemin Seo, Rory Conlin, Andrew Rothstein, SangKyeun Kim, Joseph Abbate, Azarakhsh Jalalvand, Egemen Kolemen

Proceedings of the International Joint Conference on Neural Networks, 2023

Alfvén eigenmode detection using Long-Short Term Memory Networks and CO2 Interferometer data on the DIII-D National Fusion Facility.

Alvin V. Garcia, Azarakhsh Jalalvand, Peter Steiner, Andrew Rothstein, Michael Van Zeeland, William W. Heidbrink, Egemen Kolemen

Proceedings of the International Joint Conference on Neural Networks, 2023

2022

Real-Time and Adaptive Reservoir Computing With Application to Profile Prediction in Fusion Plasma.

Azarakhsh Jalalvand, Joseph Abbate, Rory Conlin, Geert Verdoolaege, Egemen Kolemen

IEEE Trans. Neural Networks Learn. Syst., 2022

The DESC Stellarator Code Suite Part II: Perturbation and continuation methods.

Rory Conlin, Daniel W. Dudt, Dario Panici, Egemen Kolemen

CoRR, 2022

2021

Keras2c: A library for converting Keras neural networks to real-time compatible C.

Rory Conlin, Keith Erickson, Joseph Abbate, Egemen Kolemen

Eng. Appl. Artif. Intell., 2021

Neural Dynamical Systems: Balancing Structure and Flexibility in Physical Prediction.

Viraj Mehta, Ian Char, Willie Neiswanger, Youngseog Chung, Andrew Oakleigh Nelson, Mark D. Boyer, Egemen Kolemen, Jeff G. Schneider

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020

Offline Contextual Bayesian Optimization for Nuclear Fusion.

Youngseog Chung, Ian Char, Willie Neiswanger, Kirthevasan Kandasamy, Andrew Oakleigh Nelson, Mark D. Boyer, Egemen Kolemen, Jeff Schneider

CoRR, 2020

2019

Offline Contextual Bayesian Optimization.

Ian Char, Youngseog Chung, Willie Neiswanger, Kirthevasan Kandasamy, Oak Nelson, Mark D. Boyer, Egemen Kolemen

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019