Kevin W. Zhang

I am currently a fourth year undergraduate studying at the University of California, Berkeley.

I am also an undergraduate research assistant at the Berkeley Artificial Intellgence Research (BAIR) lab, working on deep self-supervised learning under Professor Alexei Efros and the formal verification of neural network controllers under Professor Gireeja Ranade.

Previously, I worked on flourescence deconvolution and MRI reconstruction with deep learning under Professor Laura Waller and Professor Michael Lustig. Additionally, I formerly taught CS 70: Discrete Mathematics and Probability Theory as a teaching assistant (TA). I was also a software engineering intern at Google doing Android development on the ridesharing team in the Google Maps divison.

Wir müssen wissen.
Wir werden wissen.

—David Hilbert

Publications (* indicates equal contribution)

Memory-efficient Learning for Large-scale Computational Imaging
Michael Kellman, Kevin Zhang, Eric Markley, Jonathan I. Tamir, Emrah Bostan, Michael Lustig, Laura Waller
IEEE Transactions on Computational Imaging, September 2020
[IEEE] [code]

3D fluorescence deconvolution with deep priors
Kevin Zhang, Michael Kellman, Emrah Bostan, Laura Waller
SPIE BiOS, Feburary 2020

Memory-Efficient Learning for Unrolled 3D MRI Reconstructions
Kevin Zhang*, Michael Kellman*, Jonathan I. Tamir, Michael Lustig, Laura Waller
ISMRM Workshop on Data Sampling and Reconstruction, January 2020
[ISMRM] [video]

Side Projects

I also enjoy building creative and visual web apps with an algorithmic emphasis. The source code for these projects is on my Github.

Tangram Generator Genetic Algorithms