Quan Sun
Research Scientist at BAAI
Beijing, United States
Summary
🤩
Rockstar🎓
Top SchoolQuan Sun is a research scientist and engineer with 8 years of experience applying machine learning and multimodal models in industry, including roles at OPPO, Amazon, and Tencent. He has a strong academic foundation in biomedical engineering from Beihang and Cornell, which informs a practical, research-driven approach to algorithm design. Quan has contributed to FlagAI by integrating EVA-CLIP—implementing transformers, attention mechanisms, and tokenizer adaptations—and writing unit tests to productionize multimodal capabilities. Equally comfortable in research and engineering settings, he has shipped recommender and large-scale model work at top tech firms and focuses on bridging prototype models to robust infrastructure. Based in Beijing with U.S. education and international industry experience, he brings cross-cultural collaboration and a knack for turning academic insights into deployable ML systems.
8 years of coding experience
2 years of employment as a software developer
Master's degree, Biomedical Engineering, Master's degree, Biomedical Engineering at Beihang UniversityMaster's degree, Biomedical Engineering, Master's degree, Biomedical Engineering at Cornell University
Github Skills (7)
transformers10
pytorch10
machine-learning10
python10
tokenizer9
computer-vision8
unit-testing8
Programming languages (2)
Github contributions (5)
FlagAI-Open/FlagAI
Nov 2022 - Jan 2023
FlagAI (Fast LArge-scale General AI models) is a fast, easy-to-use and extensible toolkit for large-scale model.
Role in this project:
ML Engineer
ML EngineerContributions:12 commits, 5 PRs in 1 month
Contributions summary:Quan primarily contributed to the implementation and testing of the EVA-CLIP model within the FlagAI framework. This involved adding the model's code, including the transformer and attention mechanisms, and writing unit tests to ensure its functionality. Furthermore, the user made modifications to existing code, such as the tokenizer, to integrate the EVA-CLIP model. The contributions demonstrate a focus on integrating multimodal models within the FlagAI ecosystem.
pytorchdeep-learningmachine-learningscaleroberta
Quan-Sun/Quan-Sun.github.io
Apr 2019 - Sep 2019
Contributions:276 pushes, 1 branch in 4 months
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