Brent Yi
PhD Candidate
Summary
🤩
RockstarMichelle Lee is an award-winning robotics researcher and entrepreneur who combines a PhD candidacy at the Stanford AI Lab with her role as CEO of Medra, bringing 10 years of cross-disciplinary experience in robotics, perception, and machine learning. Her academic work earned ICRA 2019 Best Paper and a NeurIPS Robot Learning Workshop Best Paper, while industry stints at NVIDIA, SpaceX, and McKinsey demonstrate an ability to translate research into engineering and business impact. A hands-on engineer, she contributes to high-profile open-source projects like nerfstudio—fixing numerical stability issues in Instant-NGP and eliminating memory leaks—and has helped improve both ML course sites and released vision assignments at Stanford. She also co-founded and advises startups, leveraging degrees in chemical and mechanical engineering to approach robotics problems with an uncommon blend of physical intuition and algorithmic rigor. Based in the San Francisco Bay Area, she bridges research, product, and operations to deliver robust, production-ready ML and robotics systems.
11 years of coding experience
Github Skills (21)
pytorch10
serf10
python10
css10
responsive-design10
machine-learning10
optimisation10
html10
computer-vision10
optimization10
3d-reconstruction10
website-development9
code-optimization9
segmentation9
image-segmentation9
Programming languages (18)
Github contributions (5)
StanfordVL/CS131_release
Sep 2019 - Nov 2020
Released assignments for the Stanford's CS131 course on Computer Vision.
Role in this project:
ML Engineer
ML EngineerContributions:24 commits, 10 PRs, 28 pushes in 1 year 1 month
Contributions summary:Brent released several assignments related to the CS131 course on computer vision. These releases include code and notebooks for K-Means and HAC clustering, image segmentation, and object detection utilizing techniques such as HOG feature extraction and image pyramids. The contributions involve implementing and testing algorithms for various computer vision tasks, indicating practical application of learned concepts.
stanfordpythonvisiondeep-learningcomputer-vision
nerfstudio-project/nerfstudio
Jul 2022 - Dec 2022
A collaboration friendly studio for NeRFs
Role in this project:Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:4 releases, 253 reviews, 29 commits in 5 months
Contributions summary:Brent primarily contributed to the improvement and stability of the NeRFstudio project. They fixed typos and type errors across multiple Python files and implemented code style fixes. They also addressed issues related to numerical stability in the Instant-NGP model, specifically related to truncated exponential functions. Furthermore, they updated dependencies and fixed a memory leak, demonstrating a focus on code quality and performance within the project's machine learning and rendering context.
pytorchphotogrammetrydeep-learningcomputer-vision3d-reconstruction
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