Yubei Chen

Reveal Contact Info

PhD Student

Electrical Engineering and Computer Sciences

Olshausen Lab

Current Research

I’m interested in understanding human-level intelligence. Before we can figure out the theory of mind, I believe it’s necessary to understand the patterns of signals that humans are dealing with. So at this moment, I’m working on finding the elementary mathematical structures of natural signals. There are not many of these structures and each of them is not necessarily complex. But, when these simple elements entangle with each other, things quickly exceed the ability of our imagination. My job is to identify and factorize them clearly, concisely and completely, or even uniformly and then mix them together. Thus we can build unsupervised and generative models for the signals, in a somewhat principled way. This might be the first step towards building a truly intelligent machine, which can dream as we do. To be honest, I might be looking for something that doesn’t exist though I suspect there is a hidden gem in the mist, very close.

I like Taoism in the Chinese culture and I think it’s been quite inspiring during my journey voyaging in signal spaces. My favorite philosophical point of view is that “为学日益,为道日损”. This is my light in the darkness.

Background

I received my bachelor’s degree from the electrical engineering department, Tsinghua University, Beijing in 2012. Since then, I joined the EECS department and Berkeley AI Research (BAIR) at UC Berkeley, to pursue my Ph.D. study on generative unsupervised learning models under the supervision of Professor Bruno Olshausen. Along the way, I have received my M.S. degree in EECS and M.A. degree in mathematics at Berkeley. In 2012, I was awarded the NSF GRFP fellowship. I also serve as a reviewer for NeurIPS, ICLR, ICML, AAAI, etc. When I’m away from my research, I enjoy practicing mixed martial art (MMA) and I’m an active member of the UC Berkeley Judo Team.