About Me
I am Rui Hu, an Assistant Professor in the Computer Science and Engineering Department at University of Nevada, Reno. My research mainly focuses on solving the security, privacy, and efficiency issues of machine learning, federated learning, edge computing, etc..
I am currently looking for highly self-motivated Ph.D. students for Fall 2023 (with assistantship) who are interested in working on machine learning, IoT systems, wireless communications, cyber-security, and data privacy. Please send me your CV, transcripts, TOEFL and GRE scores, and everything else that you believe will help your application if you are interested.
Education
PhD in Electrical Engineering, 2022
The University of Texas at San Antonio
BEng in Electrical Engineering, 2017
Jinan University, China
Research Interests
Federated Learning
Data Privacy & Cyber Security
Edge Computing & IoT
Wireless Communication
News
09/2023: Congratulations to Zikai for receiving the IEEE CNS student travel grant and UNR GSA Travel Award!
08/2023: Our paper on defending against byzantine attacks in federated learning has been accepted by CNS 2023. Congratulations, Zikai!
03/2023: I received the Outstanding Ph.D. Dissertation Award from UTSA!
08/2022: Our paper "Agent-Level Differentially Private Federated Learning via Compressed Model Perturbation" was accepted by IEEE CNS 2022!
05/2022: I served as a TPC member of the IEEE Consumer Communications & Networking Conference (CCNC) 2023.
05/2022: I received the Outstanding Graduate Research Award of UTSA!
04/2022: I defended my Ph.D. dissertation!
03/2022: I will join the CSE department, University of Nevada, Reno, as a tenure-track assistant professor in July 2022!
03/2022: Our paper "Energy-Efficient Distributed Machine Learning at Wireless Edge with Device-to-Device Communication" was accepted by IEEE ICC 2022!
02/2022: I served as a TPC member of the 19th Annual International Conference on Privacy, Security, and Trust (PST) 2022.
01/2022: Our paper "Hybrid Local SGD for Federated Learning with Heterogeneous Communications" was accepted by ICLR 2022 and selected for a spotlight presentation (5%).
06/2021: I served as a TPC member of IEEE Vehicular Technology Conference (VTC) 2021.
04/2021: Our paper "Federated Learning with Sparsification-Amplified Privacy and Adaptive Optimization" was accepted by IJCAI 2021 (Acceptance ratio: 13.9%).