Dogyoon Song

About

I am an Assistant Professor in the Department of Statistics at University of California, Davis.

Prior to joining UC Davis, I was a postdoctoral research fellow at the University of Michigan, hosted by Alfred O. Hero and Qing Qu. I completed my Ph.D. in Electrical Engineering and Computer Science at MIT, advised by Pablo A. Parrilo and Devavrat Shah. Also, I earned my undergraduate degrees from Seoul National University in South Korea.

My research interests broadly lie at the interface of optimization, statistics, and machine learning, with a focus on developing theories and efficient algorithms for data-assisted decision making. I am especially interested in studying the geometric principles that govern low-complexity models in high-dimensional settings, aiming to explain the performance of modern AI systems and advance decision-making tasks. Specifically, my current interests include:

• Geometry of low-complexity models
• Decision making with high-dimensional data
• Machine learning & Deep learning theory