Feijie Wu
Research Intern at Purdue University
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 (7)
federated-learning10
machine-learning9
pytorch9
fine-tuning4
llm3
p2p1
peer-to-peer1
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 - Aug 2025
An official implementation of "FedBiOT: LLM Local Fine-tuning in Federated Learning without Full Model", which has been accepted by KDD'24.
Contributions:22 pushes, 2 branches, 3 comments in 1 year 2 months
federated-learningfine-tuningllm
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