Ruiming Cao

Ph.D. student at UC Berkeley.

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I am a Ph.D. candidate at UC Berkeley, where I am advised by Prof. Laura Waller and supported, in part, by Siebel Scholarship. I am also affiliated with the Berkeley Artificial Intelligence Research (BAIR). My research focuses on motion modeling and dynamic imaging. I jointly develop methods the optical system hardware and the computational modeling and algorithms to enhance our capabilities for observing and analyzing fast and complex dynamics. I’ve worked on various image sensing modalities, including digital photography, fluorescence microscopy, label-free microscopy, medical imaging, and also emerging imaging sensors. I was a research intern in Google Research in 2021 and an optical scientist intern in Meta Reality Labs Research in 2022.

I received M.S. in Computer Science from UCLA in 2019, where I was advised by Prof. Kyung Hyun Sung and Prof. Fabien Scalzo. He received B.S. in Computer Science and Applied Mathematics from UCLA where I worked with Prof. Song-Chun Zhu.

Besides research, I spend time on skiing, running, hiking, reading. My name is pronounced as “Rei-Ming Tsao/Chao” :)

selected publications

  1. Dynamics
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    Neural space-time model for dynamic scene recovery in multi-shot computational imaging systems
    Ruiming Cao, Nikita S Divekar, James Nuñez, and 2 more authors
    bioRxiv preprint: bioRxiv 2024.01.16.575950, 2024
  2. Event Camera
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    Noise2Image: Noise-Enabled Static Scene Recovery for Event Cameras
    Ruiming Cao*Dekel Galor*, Amit Kohli, and 2 more authors
    arXiv preprint arXiv:2404.01298, 2024