Scholar
Jieming Bian
Google Scholar ID: k6E4dDwAAAAJ
Ph.D. Candidate, University of Florida
Citations & Impact
Citations
242
H-index
11
i10-index
11
Publications
20
Co-authors
9
list available
Publications
Resume (English only)
Academic Achievements
- Multiple papers accepted by top conferences such as AAAI 2026, NeurIPS 2025, and ICCV 2025. Notable works include 'FedALT: Federated Fine-Tuning through Adaptive Local Training with Rest-of-the-World LoRA', 'Adaptive LoRA Experts Allocation and Selection for Federated Fine-Tuning', and more. 'CAFE: Carbon-Aware Federated Learning in Geographically Distributed Data Centers' received a Best Paper Nomination.
Research Experience
- Will join Amazon Alexa AI as an Applied Scientist Intern this summer.
Education
- Ph.D. Candidate in Computer Engineering, University of Florida, Advisor: Prof. Jie Xu; Master's in Operations Research, Columbia University.
Background
- Research interests include Federated Learning, Parameter-Efficient Fine-Tuning (PEFT), and Large Foundation Models. Before joining the University of Florida, he was a master's student at Columbia University, majoring in Operations Research.
