Lingfei Wu
Co-Founder And CEO at Anytime AI
City of White Plains, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolLingfei Wu is a PhD-trained AI leader and entrepreneur with 11 years of experience building production-grade ML, NLP, and generative AI systems across IBM, JD.com, Pinterest, and now as Co-Founder and CEO of Anytime.AI, a startup automating plaintiff-side legal workflows. He has led large cross-functional teams to deliver business-impacting LLM and GNN products—such as JD’s JDSmartShopping and content-understanding models at Pinterest—while earning multiple invention awards and top-tier conference publications. A hands-on researcher-engineer, Lingfei has authored 60+ papers, 25+ patent filings, and contributed maintenance fixes to influential open-source projects like Graph4NLP. He combines deep technical expertise in LLMs, GNNs, and computer vision with product rigor to drive ROI-focused R&D and has a track record of translating research wins into 250%+ improvements in e-commerce metrics. Based in White Plains, NY, he brings both academic depth and startup grit to scale AI solutions in regulated domains.
10 years of coding experience
9 years of employment as a software developer
Master of Science (MS) Automation, Master of Science (MS) Automation at University of Science and Technology of ChinaDoctor of Philosophy (Ph.D.) Computer Science, Doctor of Philosophy (Ph.D.) Computer Science at William & Mary
Chinese, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (7)
pytorch10
python10
natural-language-processing9
graph-neural-network9
deeplearning-ai9
nlp9
deep-learning9
Programming languages (4)
Github contributions (5)
graph4ai/graph4nlp
Jul 2020 - Nov 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:
Back-end Developer
Back-end DeveloperContributions:3 releases, 430 commits, 113 PRs in 2 years 4 months
Contributions summary:Lingfei primarily worked on bug fixes within the dataset implementation. They reverted changes related to dataset functionalities in the `graph4nlp/pytorch/data/dataset.py` file. Additionally, they addressed issues within the summarization example, suggesting contributions to the model training and dataset handling aspects of the project. Their work primarily focused on maintaining the integrity and correctness of the dataset and example code within the project.
nlppytorchindexdeep-learningvisit
IBM/Graph2Seq
Nov 2018 - Jun 2021
Graph2Seq is a simple code for building a graph-encoder and sequence-decoder for NLP and other AI/ML/DL tasks.
Contributions:2 pushes, 7 comments in 2 years 7 months
nlpsequenceai-mlmachine-learningdecoder
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