Geo Zhou Jie Zhou
Logo Department of Computer Science and Engineering, Michigan State University

I am a Ph. D. student in the Department of Computer Science and Engineering, Michigan State University. My current research is under the supervision of Prof. Zeng, in the INSS lab. Before that, I got my master degree from University of Chinese Academy of Sciences, in Institute of Computing Technology, under the supervision of Dr. Yao. I got my bachelor degree from Beijing University of Technology.

My research interest focus on:

Wireless Sensing: Multimodal sensing using signals like mmWave, Lidar and visible light.

Deep Learning: Neural networks for sensing and planning.


Education
  • Michigan State of University
    Michigan State of University
    Department of Computer Science and Engineering
    Ph.D. Student
    Aug. 2025 - present
  • University of Chinese Academy of Sciences
    University of Chinese Academy of Sciences
    M.S. in Computer Science
    Sep. 2022 - Jul. 2025
  • Beijing University of Technology
    Beijing University of Technology
    B.S. in Electronic Engineering
    Sep. 2018 - Jul. 2022
Honors & Awards
  • Third Prize in National College Student Innovation and Entrepreneurship Annual Conference
    2022
  • Outstanding of Graduation in Beijing Univerisity of Technology
    2022
News
2025
I joined INSS lab under the supervision of Prof. Zeng in Michigan State of University.
Aug 25
I have graduated from University of Chinese Academy of Sciences and Institute of Computing Technology.
Jul 05
2022
I am pursuing Master Degree in University of Chinese Academy of Sciences, under the supervision of Dr. Ping Yao.
Sep 02
Selected Publications (view all )
Rascene: High-Fidelity 3D Scene Imaging with mmWave Communication Signals
Rascene: High-Fidelity 3D Scene Imaging with mmWave Communication Signals

KunZhe Song, Geo Jie Zhou, Xiaoming Liu, Huacheng Zeng

CVPR (Accepted) 2026

This paper introduces Rascene, a novel framework that enables high-fidelity 3D imaging by repurposing ubiquitous mmWave OFDM communication signals.

Rascene: High-Fidelity 3D Scene Imaging with mmWave Communication Signals

KunZhe Song, Geo Jie Zhou, Xiaoming Liu, Huacheng Zeng

CVPR (Accepted) 2026

This paper introduces Rascene, a novel framework that enables high-fidelity 3D imaging by repurposing ubiquitous mmWave OFDM communication signals.

All publications