Jianfeng Yan
Senior Algorithm Engineer at Tencent
Shenzhen, Guangdong Province, China
Summary
🤩
Rockstar🎓
Top SchoolJianfeng Yan is a Senior Algorithm Engineer with 11 years of experience building CV, NLP and multimodal algorithms for short-video search and recommendation, currently driving video AI research and production at Tencent’s AI Lab in Shenzhen. He combines a strong statistical foundation from Columbia (MS in Statistics) and Wuhan University with hands-on engineering—contributing PQ/LOPQ vector compression work to the GNES semantic search project to scale high-dimensional nearest-neighbor retrieval. Past roles at iQIYI and industry internships show applied expertise in conversational AI, fraud detection, and large-scale data modeling, while academic work included nonparametric regression and interactive data visualization. Colleagues know him for translating research ideas into robust, production-ready components that improve retrieval quality and efficiency.
11 years of coding experience
2 years of employment as a software developer
Bachelor in Mathmatics, GPA 3.6/4, Bachelor in Mathmatics, GPA 3.6/4 at Wuhan UniversityMaster in Statistics, 3.7/4.33, Master in Statistics, 3.7/4.33 at Columbia University in the City of New York
Github Skills (5)
approximate-nearest-neighbor-search10
python10
k-means-clustering9
dimensionality-reduction8
tensorflow5
Programming languages (2)
Github contributions (5)
gnes-ai/gnes
Feb 2019 - Sep 2019
GNES is Generic Neural Elastic Search, a cloud-native semantic search system based on deep neural network.
Role in this project:
Back-end & ML Engineer
Back-end & ML EngineerContributions:590 commits, 67 PRs, 110 pushes in 6 months
Contributions summary:Jianfeng implemented product quantization (PQ) functionality, a technique for vector compression and approximate nearest neighbor search, within the `src/nes/encoder` directory. The work includes code changes in `src/nes/encoder/pq.py`, `src/nes/encoder/lopq.py`, `src/nes/encoder/pca.py`, and `src/nes/encoder/helpers.py` along with a testing file in `tests/test_lopq.py`. The user also integrated code from an existing Python codebase for better compression of high-dimensional data.
mlpcaffe2solrsearch-engineselasticsearch
Larryjianfeng/test_swig
Mar 2019 - May 2019
Contributions:4 PRs, 10 pushes, 5 branches in 2 months
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