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Applied Physics

Gowoon Cheon

I’m a 5th year PhD student in the Materials Computation and Theory Group led by Prof. Evan Reed. My research interests are at the intersection of machine learning and physics. In particular, I aim to use machine learning to solve problems in physical sciences previously considered intractable with existing methods. These include finding new materials that can enable the next generation of scalable and flexible electronic devices using semi-supervised learning, meta learning for elucidating the phase change mechanisms in materials, and machine learning the energy landscape of crystalline materials for structure prediction. I co-host the the podcast Materials and Megabytes, which explores the development of machine learning for materials science, physics, and chemistry applications.

Before coming to Stanford, I received my BS in physics from Korea Advanced Institute of Science and Technology, and also spent a year in Karlsruhe Institute of Technology, Germany. In my free time, I enjoy drawing, beating people at eating spicy food, and pretending to be more outdoorsy than I actually am.