Shengwen Yang
Chief Scientist at HashData - SQL on Cloud
Chaoyang District, Beijing, China
Summary
🤩
Rockstar🎓
Top SchoolShengwen Yang is a Chief Scientist with 13 years of experience building large-scale data and AI systems, currently leading HashData’s effort to embed advanced LLM and ML capabilities directly into the enterprise data warehouse. His background spans research and product leadership at Baidu (chairing its Big Data technical committee), Pivotal/Greenplum, Yahoo, and HP Labs, with deep expertise in user profiling, recommendation, advertising science, and MPP/Hadoop analytics. He holds a Ph.D. from Tsinghua and combines academic rigor with hands-on systems design—driving both distributed compute infrastructure and user-facing AI agents like DataMind and DocMind. Notably, he bridges SQL-first analytics and developer workflows via dual Python and SQL ML interfaces, enabling non-ML users to invoke sophisticated models inside their queries. Based in Chaoyang District, Beijing, he focuses on practical R&D that turns cross-product behavioral data into actionable intelligence for finance, insurance, and retail.
13 years of coding experience
7 years of employment as a software developer
M.S., Telecommunication, M.S., Telecommunication at Northeastern University (CN)Ph.D., Computer Science, Ph.D., Computer Science at Tsinghua University
Stackoverflow
1reputation
0reached
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Github Skills (66)
gbm10
xgboost10
parallel10
dataflow10
python10
feature-extraction10
hyperparameter-optimization10
deep-learning10
automl10
ray10
optimization10
portable10
representation-learning10
deepar10
gradient-boosting10
Programming languages (5)
Github contributions (5)
yangs16/xgboost
Jun 2016 - Nov 2016
Contributions:2 PRs, 31 pushes, 4 branches in 5 months
pythonflinkdataflowgbmbig-data
yangs16/ray
Mar 2023 - Apr 2023
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads.
Contributions:14 pushes, 6 branches in 4 days
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