Theoretical investigation of correlated electron phenomena; high Tc superconductivity; topological phenomena; phase detection, using machine learning
Current Research Interest
Predictive design of new exotic superconductors; intertwined orders in high Tc superconductors; topological quantum criticality; phase detection using neural network-based machine learning
Simons Foundation Fellow in Theoretical Physics
Department of Energy Early Career Award
National Science Foundation Early Career Award
Zhang, Yi and Eun-Ah Kim. “Quantum Loop Topography for Machine Learning.” Physics Review Letters 118 (2017): 216401.
Hsu, Yi-Ting, Abolhassan Vaezi, Mark H. Fischer, and Eun-Ah Kim. “Topological Superconductivity in Monolayer Transition Metal Dichalcogenides.” Nature Communications 8 (2017): 14985.