Jerry Mei
Research Assistant at Princeton University
New Jersey, United States
Summary
👤
Senior🎓
Top SchoolJerry Mei is a Princeton Ph.D. candidate in Computer Science and experienced research engineer with eight years of work spanning MIT CSAIL and Princeton, focused on computational perception and generative modeling. He has contributed to high-profile projects like Infinigen—building procedural, photorealistic worlds—and to cognitive-science-informed endeavours such as ADEPT and FALCON, reflecting a blend of computer vision, graphics, and cognitive modeling. With dual foundations in mathematics and computer science from Peking University and MIT (MEng), he brings rigorous theoretical training to practical system-building and backend development. An IMO gold medalist, Jerry combines mathematical creativity with engineering discipline, often contributing automated, reproducible tooling and configuration work that scales complex scene-generation pipelines.
8 years of coding experience
4 years of employment as a software developer
Bachelor of Science - BS, Mathematics 18, Computer Science 6-3, Bachelor of Science - BS, Mathematics 18, Computer Science 6-3 at Massachusetts Institute of TechnologyBachelor's degree, Mathematics, Bachelor's degree, Mathematics at Peking UniversityDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Princeton University
Chinese, English
Github Skills (3)
procedural-generation10
python10
3d-rendering9
Programming languages (7)
Github contributions (5)
princeton-vl/infinigen
Jun 2023 - May 2025
Infinite Photorealistic Worlds using Procedural Generation
Role in this project:
Back-end Developer
Back-end DeveloperContributions:2 comments in 1 year 11 months
Contributions summary:The user, Lingjie Mei, contributed to procedural generation within the Infinigen project. Their work focused on modifying and adding to the world generation configuration files and Python files related to generating photo-realistic worlds. The changes included modifications to scene types (kelp forests, deserts, etc.), the addition of components and functions for rendering and generating various assets (kelp, marine snow, jellyfish, etc.). These contributions were made through multiple automated commits indicating authorship.
procedural-generation
JerryLingjieMei/ADEPT-Dataset-Release
Aug 2019 - Sep 2022
This is the dataset generation code for ADEPT (Approximate Derenderer, Extended Physics, and Tracking). http://physadept.csail.mit.edu/
Contributions:6 commits, 4 pushes in 3 years 1 month
dataset-generation
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