Wenzhao Zheng
Postdoctoral Researcher at University of California, Berkeley
Berkeley, California, United States
Summary
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Rockstar🎓
Top SchoolWenzhao Zheng is a postdoctoral researcher at UC Berkeley’s EECS department affiliated with BAIR and BDD, bringing seven years of experience at the intersection of computer vision and AI for autonomous systems. He earned a PhD in Artificial Intelligence from Tsinghua University after a physics and mathematics undergraduate foundation, and has transitioned academic research into practical model implementations such as TPVFormer, an occupancy-network-style approach for autonomous driving with public code and visualization tools. Supervised by leading researchers, he blends rigorous theoretical training with hands-on engineering to improve model interpretability and deployment readiness. Based in Berkeley, he combines deep learning research with a knack for producing reproducible, well-documented code that bridges labs and real-world driving applications.
7 years of coding experience
1 year of employment as a software developer
Zhengzhou No.1 High SchoolDoctor of Philosophy - PhD, Artificial Intelligence, Doctor of Philosophy - PhD, Artificial Intelligence at Tsinghua University
Chinese, English
Github Skills (9)
transformer-models10
computer-vision10
pytorch10
deep-learning10
python10
autonomous-driving10
visualizations9
machine-learning9
visualization9
Programming languages (1)
Github contributions (5)
wzzheng/TPVFormer
Nov 2022 - Mar 2023
[CVPR 2023] An academic alternative to Tesla's occupancy network for autonomous driving.
Role in this project:
ML Engineer
ML EngineerContributions:29 commits, 24 pushes, 1 branch in 3 months
Contributions summary:Wenzhao appears to be focused on implementing and refining the TPVFormer model for autonomous driving, an occupancy network. Their initial contribution involves releasing the foundational code for the model. Subsequent work includes merging changes and adding visualization capabilities, indicating efforts to improve model functionality and interpretability. These contributions demonstrate the user's involvement in both the core model development and the visualization aspects of this project.
wzzheng/HDML
Mar 2019 - Apr 2020
Contributions:35 commits, 5 pushes, 16 comments in 1 year
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