Shuai Tang
Summary
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SeniorShuai Tang is a quantitative researcher with a Ph.D. in Cognitive Science from UC San Diego and a decade of experience applying representation learning and ML to real-world systems. He has transitioned from academic work in unsupervised and neural representation learning to applied roles at AWS—contributing to Transformer-based generation for CodeWhisperer and differential privacy in AWS Clean Rooms—and now conducts quantitative research at Jump Trading. Shuai blends rigorous theory (unsupervised learning, sparse representations, optimization) with production-focused applied science, shipping models and privacy-aware systems at scale. His background includes multiple industry research internships (Microsoft, Adobe, Tencent) and teaching deep learning and unsupervised learning courses, signaling both breadth and the ability to communicate complex ideas. Based in New York, he brings a researcher’s curiosity to high-frequency decision environments, often approaching model design with efficiency and interpretability in mind.
11 years of coding experience
Github Skills (37)
python9
machine-learning9
gpu9
jax8
deep-learning8
ai8
numpy8
google8
neural-network8
tensor7
notebook7
mxnet7
gpu-acceleration7
jit7
julia7
Programming languages (5)
Github contributions (5)
shuaitang/TPRU
Jan 2019 - May 2019
Contributions:29 commits, 20 pushes, 1 branch in 3 months
shuaitang/Slides
Dec 2017 - Feb 2019
Contributions:9 pushes, 1 branch in 1 year 2 months
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