Nan Wang
Co-Founder & CTO at Jina AI
Haidian District, Beijing, China
Summary
🤩
Rockstar🎓
Top SchoolNan Wang is an experienced machine learning researcher and engineer with 12 years in the internet industry, combining a Ph.D. in Computational Neuroscience & Machine Learning with hands-on backend work in production AI systems. As an ex-CTO and co-founder affiliated with Jina AI, Nan has contributed notable open-source improvements to Jina's serve and examples repositories, adding transformer encoders, fixing model-loading/mask bugs, and modernizing example apps like urbandict-search. Comfortable bridging research and engineering, Nan focuses on multimodal model integration, encoder design, and scalable indexing/query pipelines. Based in Haidian, Beijing, Nan’s background in mechatronics and robotics gives an uncommon systems perspective on model deployment and real-world data flows.
12 years of coding experience
10 years of employment as a software developer
Bachelor’s Degree, Mechatronics, Robotics, and Automation Engineering, Bachelor’s Degree, Mechatronics, Robotics, and Automation Engineering at East China University of Science and TechnologyDoctor of Philosophy (Ph.D.), Computational Neuroscience & Machine Learning, Doctor of Philosophy (Ph.D.), Computational Neuroscience & Machine Learning at Ruhr-Universität Bochum
Chinese, German, English
Github Skills (14)
transformer-models10
jina10
encode10
python10
semantic-search10
encoder10
tensorflow9
nlp9
deep-learning9
machine-learning8
dockers7
docker7
fastapi7
deeplearning-ai7
Programming languages (8)
Github contributions (5)
jina-ai/examples
Mar 2020 - Sep 2021
Jina examples and demos to help you get started
Role in this project:
Back-end Developer
Back-end DeveloperContributions:164 reviews, 203 commits, 279 PRs in 1 year 6 months
Contributions summary:Nan primarily contributed to the development of the "urbandict-search" example. Their work focused on implementing features, including adding indexing and query functionality. They made changes to key files like `customized_executors.py` and `query.py`, which suggests interaction with Jina's executor framework and core application logic. Furthermore, the user adapted the project to newer versions of the Jina framework and refactored code.
nlppythononboardingget-starteddeep-learning
jina-ai/serve
Feb 2020 - Dec 2022
☁️ Build multimodal AI applications with cloud-native stack
Role in this project:Back-end Developer
Back-end DeveloperContributions:5 releases, 530 reviews, 469 commits in 2 years 10 months
Contributions summary:Nan's contributions focused on adding and improving the encoder functionality within the "serve" repository, which builds multimodal AI applications. They addressed bugs in drivers related to CompoundExecutor and implemented transformer encoders, including related test cases and documentation. Their work involved refactoring codes and fixing issues in masks and model loading, suggesting a strong understanding of transformer-based models.
opentelemetryllm-inferencecreative-aigrpcproduction
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