Offline Contextual Bayesian Optimization. - Ian Char; Youngseog Chung; Willie Neiswanger; Kirthevasan Kandasamy; Oak Nelson; Mark D. Boyer; Egemen Kolemen (NeurIPS, 2019)

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 001 (CoRR, 2020)

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 (CDC, 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)

The DESC Stellarator Code Suite Part II: Perturbation and continuation methods. - Rory Conlin; Daniel W. Dudt; Dario Panici; Egemen Kolemen (CoRR, 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)

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 (IJCNN, 2023)

Multimodal Prediction of Tearing Instabilities in a Tokamak. - Jaemin Seo; Rory Conlin; Andrew Rothstein; SangKyeun Kim; Joseph Abbate; Azarakhsh Jalalvand; Egemen Kolemen (IJCNN, 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 (L4DC, 2023)

Stellarator Optimization with Constraints. - Rory Conlin; Patrick Kim; Daniel W. Dudt; Dario Panici; 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)

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)

High Order Free Boundary MHD Equilibria in DESC. - Rory Conlin; Jonathan Schilling; Daniel W. Dudt; Dario Panici; Rogerio Jorge; Egemen Kolemen (CoRR, 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)

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)

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)

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 G. Schneider (CoRR, 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, 2025)