Yang Wang
Data Scientist
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
Master of Science (M.S.), Statistics, Master of Science (M.S.), Statistics 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 (20)
pytorch10
distributed-training10
parallel10
python10
machine-learning10
industrial10
reinforcement-learning10
deep-learning10
tensorflow10
gpu10
neural-network10
paddlepaddle10
scalability10
numpy9
acceleration9
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
memory-efficientcaffe2paralleldeep-learningpaddlepaddle
wangyang59/book
Dec 2016 - Mar 2017
Contributions:1 PR, 20 pushes, 2 branches in 2 months
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