Zirui Wang

Rehg's Lab Research Intern at University of Illinois Urbana-Champaign

Champaign, Illinois, United States
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Summary

👤
Senior
🎓
Top School
Zirui Wang is a computer vision researcher and MS student at UIUC with nine years of practical experience building 3D generation and vision-language systems. Currently a research intern in Prof. James Rehg’s lab, he has contributed to GenAI projects and previously developed multimodal Vision-Language-Action models for autonomous driving at XPENG and multi-agent anticipation at CMU’s Robotics Institute. His background spans industry and research internships—from camera algorithm optimization at OmniVision to automated feature extraction for critical mineral maps at NCSA—demonstrating strengths in applied deep learning and geospatial vision. Comfortable moving between research and production settings, Zirui also maintains a personal academic homepage and actively explores intersections of 3D vision and language grounding.
code9 years of coding experience
job1 year of employment as a software developer
bookHigh School Diploma Advanced Placement, High School Diploma Advanced Placement at The High School Affiliated to Renmin University of China
bookMaster of Science - MS Computer Science, Master of Science - MS Computer Science at University of Illinois Urbana-Champaign
bookBachelor of Science - BS Computer Science, Bachelor of Science - BS Computer Science at Zhejiang University
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Github Skills (66)

radiance10
depth-estimation10
neural-rendering10
camera10
computer-vision10
3d-reconstruction10
photogrammetry10
raycasting10
pangolin10
arxiv10
depth10
mesh9
simulations9
topological-data-analysis9
3d9

Programming languages (4)

TypeScriptC++Jupyter NotebookPython

Github contributions (5)

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Ryan-Zirui-Wang/flownet3d

May 2019 - Oct 2019

Contributions:119 pushes, 30 branches, 5 tags in 4 months
ActiveVisionLab/nerfmm

Feb 2021 - Aug 2022

(Arxiv 2021) NeRF--: Neural Radiance Fields Without Known Camera Parameters
Contributions:15 commits, 20 pushes, 56 comments in 1 year 6 months
parametersarxivdeep-learningcameraneural-radiance-fields
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