About

I am a second-year Ph.D. student with Prof. Chen Chen at the University of Central Florida. I earned my Master of Science of Computer Science at the University of Rochester, advised by Prof. Chenliang Xu. Before my graduate education, I earned my Bachelor’s Degree in Computer Science at the University of Missouri, advised by Prof. Dong Xu, and my Bachelor’s Degree in Computer Science and Technology at Shandong University. My research interests include Federated Learning, Self-supervised Learning, Multi-modality Learning, Few-shot Learning, and Efficient Fine-tuning.

News

• [Apr. 2024] Our papers Towards Multi-modal Transformers in Federated Learning and Navigating Heterogeneity and Privacy in One-Shot Federated Learning with Diffusion Models are available on arXiv.
• [Aug. 2023] Our paper FedPerfix: Towards Partial Model Personalization of Vision Transformers in Federated Learning is available on arXiv.
• [July. 2023] Our paper FedPerfix: Towards Partial Model Personalization of Vision Transformers in Federated Learning has been accepted on ICCV 2023! Code and paper will be available soon.
• [Nov. 2022] Our paper Conquering the Communication Constraints to Enable Large Pre-Trained Models in Federated Learning is now available on arXiv.
• [May 2022] I've earned my Master of Science in Computer Science degree at the University of Rochester!
• [Mar. 2022] I will join Prof. Chen Chen's group as a Ph.D. student in 2022 Fall!