Tao Wang
Software Engineer at Uber
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolTao Wang is a software engineer with 10 years of experience specializing in data platforms, computation, and optimization, currently building scalable data infrastructure at Uber in the San Francisco Bay Area. He brings deep expertise in big data engines (Spark, Flink, Presto), columnar storage formats (ORC, Parquet), and workflow orchestration with Airflow, paired with practical performance tuning experience from earlier roles. His background spans high-throughput fintech and gaming systems at Visa and Electronic Arts, and he holds a CS master's from Texas A&M. An active open-source contributor, he added a model comparator and transformation utilities to the popular AutoKeras project, reflecting an ability to bridge ML tooling and production data systems. Colleagues rely on him for pragmatic optimizations that measurably reduce cost and latency while enabling large-scale analytics.
10 years of coding experience
4 years of employment as a software developer
Bachelor's degree, Electrical, Electronics and Communications Engineering, 3.83, Bachelor's degree, Electrical, Electronics and Communications Engineering, 3.83 at Beijing University of Posts and TelecommunicationsMaster's degree, computer science, Master's degree, computer science at Texas A&M University
Chinese, engllish
Github Skills (8)
keras10
machine-learning10
deep-learning10
automl10
python10
tensorflow9
dropout8
neural-architecture-search8
Programming languages (3)
Github contributions (5)
keras-team/autokeras
Dec 2017 - Jan 2018
AutoML library for deep learning
Role in this project:
ML Engineer
ML EngineerContributions:17 commits, 6 pushes, 1 branch in 20 days
Contributions summary:Tao contributed to the `keras-team/autokeras` repository, an AutoML library for deep learning, by implementing a model comparator feature. This involved creating a `comparator.py` file to compare the architecture and configurations of different neural networks. The user also wrote and tested the comparator, ensuring it correctly identifies differences between models. Furthermore, the user worked on the `net_transformer`, which suggests work related to model transformation and modification.
pytorchpythondeep-learningautomated-machine-learningneural-architecture-search
taobupt/taobupt.github.com
Aug 2015 - May 2019
Contributions:243 pushes, 1 branch in 3 years 9 months
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