Feijie Wu
Graduate Research Assistant
West Lafayette, Indiana, United States
Summary
🤩
Rockstar🎓
Top SchoolFeijie Wu is a Ph.D. candidate at Purdue University specializing in advancing large language models through federated learning, large-scale optimization, and multi-agent LLM systems. With eight years of research and engineering experience, he has interned at Microsoft, Apple, and Alibaba and contributed to about 20 publications including a Best Student Paper award. His work bridges theory and practice, tackling distributed-data challenges for LLMs and exploring tool-use AI agents and large-scale distributed systems. Feijie’s background spans top academic programs in Hong Kong, Twente, and Purdue, and he has been repeatedly invited to review for ICML, NeurIPS, ICLR, and KDD. Notably, he has a track record of industrial collaborations during his Ph.D., turning research insights into applied ML solutions. Based in West Lafayette, he combines rigorous mathematical training with hands-on systems experience to push toward scalable, privacy-aware LLM deployments.
8 years of coding experience
3 years of employment as a software developer
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at The Hong Kong Polytechnic UniversityTechnical Computer Science, Technical Computer Science at University of TwenteDoctor of Philosophy - PhD, Electrical and Electronics Engineering, Doctor of Philosophy - PhD, Electrical and Electronics Engineering at Purdue University
Github Skills (9)
data-privacy9
federated-learning9
pytorch9
machine-learning8
distributed-computing8
federated8
deep-learning7
peer-to-peer1
p2p1
Programming languages (1)
Github contributions (5)
HarliWu/FederatedScope
Jun 2023 - Aug 2023
An easy-to-use federated learning platform
Contributions:56 pushes, 2 branches in 2 months
HarliWu/FedBiOT
Jun 2024 - Mar 2025
Contributions:22 pushes, 2 branches, 2 comments in 8 months
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