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Fei Dou

Federated Learning Reinforcement Learning Self-Supervised Learning Internet Of Things (IoT) Cyber-Physical Systems (CPS)
University of Georgia School of Computing

About

Fei Dou is an Assistant Professor in the School of Computing at the University of Georgia. She obtained her Ph.D. in 2023 from the Department of Computer Science and Engineering at the University of Connecticut, where she worked in the Laboratory of Machine Learning & Health Informatics under the supervision of Prof. Jinbo Bi. Her work contributed to fundamental Machine Learning (ML) research for the Internet of Things (IoT) and Cyber-Physical Systems (CPS), particularly in the areas of federated learning, reinforcement learning, and self-supervised learning. Fei’s research focuses on advancing Machine Intelligence for Ubiquitous Computing in Distributed Systems, with an emphasis on scalable, responsible, and context-aware AI solutions.

Research Performance Summary

30
Total Papers
327
Total Citations
9
H-Index
2013-2026
Active Research Span

First Recorded Paper

基于运动预测的水下传感器网络 MAC 协议

Year: 2013

Citations: 11

Venue: 电子与信息学报 35 (3)

Latest Recorded Paper

LARV: Data-Free Layer-wise Adaptive Rescaling Veneer for Model Merging

Year: 2026

Citations: 0

Venue: arXiv preprint arXiv:2602.09413

Last 10 Years Publication Activity

This timeline shows the professor's yearly publication activity.

2026
1
2025
8
2024
6
2023
6
2020
1
2018
1
2017
1
2015
4
2013
2

Publication Venues and Collaboration

Journal, Conference, and Book Publication Breakdown

Conference 13
Journal 5
Book 0

Top Coauthors

Dou Liu Zhang

Research Impact by Period

2025-2026

Period Stats
Papers 9
Citations 25
Avg. Citations / Paper 2.8
H-Index 3

2020-2024

Period Stats
Papers 13
Citations 214
Avg. Citations / Paper 16.5
H-Index 6

2015-2019

Period Stats
Papers 6
Citations 71
Avg. Citations / Paper 11.8
H-Index 3

2010-2014

Period Stats
Papers 2
Citations 17
Avg. Citations / Paper 8.5
H-Index 2

Contact and Professional Links

Contact Information

fei.dou@uga.edu

Detected Research Keywords

Underwater Wireless Sensor Wireless Sensor Networks Reinforcement Learning Approach Underwater Sensor Networks Mobilizing Personalized Federated Personalized Federated Learning Random Walk Stochastic Walk Stochastic Admm Event Triggered Sensor