Yang Wang
Research Scientist at Meta
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolYang Wang is a data scientist with nine years of experience applying statistical modeling and large-scale optimization to digital marketing problems at Adobe. He combines a strong academic foundation—a PhD in Physics and an MS in Statistics from UC Berkeley—with practical expertise in big data systems and probabilistic models. Early research work includes scalable, MPI-based implementations of labeled LDA and knowledge-graph–enhanced topic labeling for news clustering and trend detection. Yang is comfortable bridging research and production, turning complex Bayesian and machine-learning methods into deployable analytics that drive marketing decisions. Based in the San Francisco Bay Area, he brings a physicist’s rigor to messy real-world data and a track record of hyperparameter-tuned solutions at scale.
9 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Physics, Doctor of Philosophy (Ph.D.), Physics at University of California, BerkeleyBachelor of Science (B.S.), Mathematics and Physics, Bachelor of Science (B.S.), Mathematics and Physics at Tsinghua University
Github Skills (17)
distributed-training10
python10
machine-learning10
deep-learning10
gpu10
neural-network10
paddlepaddle10
scalability10
numpy9
autograd9
tensor9
gpu-acceleration9
inference2
pytorch2
operator2
Programming languages (3)
Github contributions (5)
wangyang59/Paddle
Oct 2016 - Apr 2018
PArallel Distributed Deep LEarning
Contributions:95 pushes, 20 branches in 1 year 6 months
deep-learning
wangyang59/book
Dec 2016 - Mar 2017
Contributions:1 PR, 20 pushes, 2 branches in 2 months
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