Yu Chen
Co-founder And VP Of Engineering at Anytime AI
Sunnyvale, California, United States
Summary
🤩
Rockstar🎓
Top SchoolYu Chen is an AI researcher-turned-founder with 12 years of experience who combines deep academic credentials (PhD, 30+ top-tier papers, 2,400+ citations and multiple best-paper awards) with hands-on product execution as Co-founder and VP of Engineering at Anytime AI. He has led global engineering teams to deploy generative AI for legal workflows targeting 1.3M lawyers, while previously driving applied NLP and multimodal recommender research at Meta/Facebook and shipping customized LLM solutions. An active open-source contributor and core author of the widely used Graph4NLP library and a bestselling GNN textbook, he consistently bridges graph neural networks and NLP in both research and engineering. He also holds four US patent co-inventions and has translated his work into broad media coverage and investor traction, reflecting a rare blend of technical depth, product impact, and public influence.
12 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Computer Science, Doctor of Philosophy (Ph.D.) Computer Science at Rensselaer Polytechnic InstituteExchange student Computer & Information Science, Exchange student Computer & Information Science at University of Michigan-DearbornNingbo Xiaoshi High SchoolBachelor's Degree Telecommunications Engineering, Bachelor's Degree Telecommunications Engineering at University of Electronic Science and Technology of China
Chinese, English
Github Skills (11)
pytorch10
nlp10
graph-neural-network10
python10
natural-language-processing10
gnn10
bilstm9
word-embeddings9
machine-learning8
ml8
bert8
Programming languages (4)
Github contributions (5)
graph4ai/graph4nlp
Jul 2020 - Dec 2022
Graph4nlp is the library for the easy use of Graph Neural Networks for NLP. Welcome to visit our DLG4NLP website (https://dlg4nlp.github.io/index.html) for various learning resources!
Role in this project:
Backend Developer
Backend DeveloperContributions:10 reviews, 262 commits, 42 PRs in 2 years 5 months
Contributions summary:Yu added the core files, base classes, and utilities necessary for graph embedding construction, including classes for Glove and BERT embeddings, and BiLSTM embedding layers. Their contributions involved establishing the initial structure for the graph neural network (GNN) module and integrating it within the overall architecture. They implemented core logic for initializing graph embeddings and enabling the utilization of various embedding strategies, like Word2Vec (w2v).
nlppytorchindexdeep-learningvisit
hugochan/AI-Papers
May 2017 - Jul 2017
Contributions:34 commits, 32 pushes, 1 branch in 2 months
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