Christopher Yeh
Cypress, California, United States
Summary
🤩
Rockstar🎓
Top SchoolChristopher Yeh is a machine learning scientist and software engineer with 11 years of experience applying AI to global challenges like poverty, conservation, and climate resilience. He holds advanced degrees from Stanford and Caltech and has published high-impact work using satellite imagery to predict economic well-being, including a Nature Communications paper and SustainBench benchmarks. His background spans research internships at Microsoft, NIST, and X (formerly Google X), practical ML engineering improvements to libraries like TensorLy, and front-end documentation work on influential CS resources. A Caltech teaching award recipient, he blends deep technical rigor with teaching and product-focused implementation, and has a track record of improving model reliability and uncertainty quantification for real-world forecasting and conservation systems.
11 years of coding experience
7 years of employment as a software developer
Master of Management Science Global Affairs, Master of Management Science Global Affairs at Schwarzman ScholarsCalifornia Institute of TechnologyHigh School Diploma Valedictorian, High School Diploma Valedictorian at Los Alamitos High SchoolM.S. Computer Science, M.S. Computer Science at Stanford University
Chinese, Spanish
Github Skills (12)
tensorrt10
css10
machine-learning10
tensor10
python10
jekyll10
algebra10
documentation10
decomposition10
numpy9
front-end-development9
html8
Programming languages (15)
Github contributions (5)
ermongroup/cs228-notes
Feb 2017 - Jul 2021
Course notes for CS228: Probabilistic Graphical Models.
Role in this project:
Technical Writer & Frontend Developer
Technical Writer & Frontend DeveloperContributions:1 review, 70 commits, 61 PRs in 4 years 6 months
Contributions summary:Christopher primarily focused on improving the documentation and structure of the course notes, as evidenced by the edits to CSS files, layouts, and includes. They also made various updates to the visual presentation of the notes, including the incorporation of the Tufte theme and image inclusion. These changes suggest a focus on enhancing the readability and visual appeal of the course materials.
notesgraphical-modelsmachine-learninggraphicalprobabilistic-graphical
tensorly/tensorly
Mar 2021 - Mar 2021
TensorLy: Tensor Learning in Python.
Role in this project:ML Engineer
ML EngineerContributions:6 commits, 1 PR, 3 comments in 1 day
Contributions summary:Christopher primarily contributed to bug fixes and improvements within the `tensorly` repository, which focuses on tensor learning in Python. Their commits centered on correcting typos, addressing bugs related to the symmetric power iteration algorithm, and updating the power_iteration function to match the symmetric version. The user's work modified core decomposition functions, indicating a focus on improving the accuracy and functionality of tensor decomposition methods. They also applied code review suggestions.
tensor-factorizationtensor-decompositionpythontensor-learningtensor
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.