Chen, Yubei - GGAM Faculty

Electrical and Computer Engineering

Area of Interest

Chen's research exists at the intersection of computational neuroscience and deep unsupervised learning. His aim is to provide insights into the computational principles governing unsupervised learning in both brains and machines and to reshape our insights into natural signal statistics, a field that explores the structure of and how to model natural signals, like those that help the brain parse out the dimensions of its physical environment. At the University of California, Davis, he has identified two core missions for his research program. One is to bridge the gap between engineering and science to facilitate advancements in AI. The other is to push the frontier of unsupervised learning in machines with world models built upon sensory, motor and memory representations.

Courses Related to Research Interests

EEC 258 - Introduction to Unsupervised Learning; EEC 289A - Embodied AI and World Models; EEC 266 - Information Theory and Coding; EEC 256 - Reinforcement Learning; ECS 174 - Computer Vision; ECS 171 - Machine Learning; ECS 170 - Introduction to Artificial Intelligence; ECS 270 - Artificial Intelligence