Yubei Chen

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Postdoctoral Scholar

Olshausen Lab

Current Research

I have long been obsessed with unsupervised learning. For more than a decade, I’ve been seeking the principles governing representation learning in human brains and machine learning models. While the empirical advancements in deep learning are tremendous, our understanding and true knowledge about the representation are yet limited. In order to move further, I believe it’s necessary to invest my time to discover the principles, or 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 our imagination’s ability. My job is to identify and factorize them clearly, concisely, and completely. I am extremely grateful to receive much help from many great minds along my journey, and I wish to produce some original ideas to entertain my audience.

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

Ph.D. in Electrical Engineering and Computer Science, UC Berkeley, 2019
             with Designated Emphasis in Communication, Computation, and Statistics
M.A. in Pure Mathematics, UC Berkeley, UC Berkeley, 2014 – 2015
M.S. in Electrical Engineering and Computer Science, UC Berkeley, 2012 – 2015
B.E. in Electrical Engineering, Tsinghua University, Beijing, 2008 – 2012

I received my bachelor’s degree from the Electrical Engineering department at Tsinghua University, Beijing in 2012. Then, I joined the EECS department and Berkeley AI Research (BAIR) at UC Berkeley, to pursue my Ph.D. study on unsupervised learning and generative 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. In 2019, I got my Ph.D. from the EECS department. In late 2020, I started to work with Yann LeCun at FAIR as a postdoctoral scholar where I continue to work on unsupervised representation learning. I also serve as a reviewer for NeurIPS, ICLR, ICML, AAAI, CVPR, Neural Computation, 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.