Publications

Work on learning quantum structure from measurements, monitored dynamics, robustness, and hardware-aware quantum compilation.

My name is shown in bold. An up-to-date citation record is available on Google Scholar.

Publications and preprints

1. 2026
   Learning from almost nothing: How neural networks survive heavy input corruption
   Justin Tahmassebpur, Asadullah Bhuiyan, Hyejin Kim, and Omri Lesser
   arXiv:2606.11319
   arXiv
2. 2025
   Learning measurement-induced phase transitions using attention
   Hyejin Kim, Abhishek Kumar, Yiqing Zhou, Yichen Xu, Romain Vasseur, and Eun-Ah Kim
   arXiv:2508.15895 · under review at PRX Intelligence
   arXiv
3. 2025
   Attention to quantum complexity
   Hyejin Kim, Yiqing Zhou, Yichen Xu, Kaarthik Varma, Amir H. Karamlou, Ilan T. Rosen, Jesse C. Hoke, Chao Wan, Jin Peng Zhou, William D. Oliver, Yuri D. Lensky, Kilian Q. Weinberger, and Eun-Ah Kim
   Science Advances 11, eadu0059
   Journal
4. 2022
   Minimal neural network to learn the metal-insulator transition in the dynamical mean-field theory
   Hyejin Kim, D. Kim, and Dong-Hee Kim
   New Physics: Sae Mulli 72, 487-494
   Journal · Code

Manuscript in preparation

1. 2026
   Reinforcement learning for hardware-aware reconfigurable atom array compilation
   Hyejin Kim, Yichen Xu, Jin Peng Zhou, and Eun-Ah Kim
   Manuscript in preparation