The focus of my research has been on exploiting prior knowledge to improve machine learning systems through a fundamental understanding of deep neural networks. Specifically, I am interested in analyzing the properties of neural networks for proteins, aiming to build generalizable models that can tackle protein design problems by only utilizing small amounts of data. I joined Prescient Design in 2023. Prior to this, I received my Ph.D. from Yonsei University in South Korea.
At Prescient, my area of focus is building self-supervised learning methods for proteins. We expect that a wide range of downstream tasks, including protein design and affinity prediction, can be improved by exploiting such methods.