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Founded Projects
Founded Projects
RET Site: Research Experience on Edge Artificial Intelligence for Nevada Teachers
RET Site: Research Experience on Edge Artificial Intelligence for Nevada Teachers
Orgnization: National Science Foundation (NSF)
Amount: $600,000
Duration: 10/2025-12/2028
My role: Principal Investigator (PI)
Project Outcomes: Ongoing.
Research Infrastructure: MRI: Acquisition of a High-Performance GPU Cluster for Large-Scale AI
Research Infrastructure: MRI: Acquisition of a High-Performance GPU Cluster for Large-Scale AI
Orgnization: NSF
Amount: $597,771
Duration: 09/2025-08/2028
My role: Co-PI
Project Outcomes: Ongoing.
Federated Wildfire Data Analysis Framework based on Edge Computing and Machine Learning
Federated Wildfire Data Analysis Framework based on Edge Computing and Machine Learning
Orgnization: NSF EPSCoR HDRFS Seed Grant
Amount: $30,000
Duration: 06/2024-06/2025
My role: PI (solo)
Project Outcomes:
Publications: Published three conference papers at WACV 2025, CVPR 2025, and ACM MobiHoc 2025, and one journal paper in IEEE TNNLS. The research topics include robust and efficient federated learning, as well as the fine-tuning of large foundation models.
Open-Source Development: Developed and released an open-source codebase for a federated wildfire detection algorithm based on the Vision Transformer (ViT) model. Code: https://github.com/TNI-playground/HDRFS_wildfire_classification
Robotics and AI Curriculum Development for Undergraduate and Graduate Students at UNR College of Engineering
Robotics and AI Curriculum Development for Undergraduate and Graduate Students at UNR College of Engineering
Orgnization: NASA Space Grant
Amount: $50,000
Duration: 06/2024-06/2025
My role: Co-PI
Project Outcomes:
Curriculum Development: Developed new, computationally intensive ML projects for the CS 345 CyberAI course that were previously not feasible. This was made possible by providing students with Google Colab Pro resources, which significantly enhanced hands-on learning in cybersecurity and artificial intelligence.
Selected Papers in Refereed Journals:
Selected Papers in Refereed Journals:
Federated Learning with Sparsified Model Perturbation: Improving Accuracy under Client-level Differential Privacy
R. Hu, Y. Gong, and Y. Guo
IEEE Transactions on Mobile Computing (TMC), 2023.
Personalized Federated Learning with Differential Privacy
R. Hu, Y. Guo, H. Li, Q. Pei, and Y. Gong
IEEE Internet of Things Journal (IoT-J), 2020.
Concentrated Differentially Private Federated Learning with Performance Analysis
R. Hu, Y. Guo and Y. Gong
IEEE Open Journal of the Computer Society (OJ-CS), 2021.
DP-ADMM: ADMM-based Distributed Learning with Differential Privacy
Z. Huang, R. Hu, Y. Guo, E. Chan-Tin, Y. Gong
IEEE Transactions on Information Forensics and Security (TIFS), 15, pp.1002-1012.
Selected Papers in Refereed Conferences:
Selected Papers in Refereed Conferences:
Byzantine-Robust Federated Learning with Variance Reduction and Differential Privacy
Z. Zhang and R. Hu
IEEE Conference on Communications and Network Security (CNS), Orlando, FL, USA, Oct. 2-5, 2023
Agent-Level Differentially Private Federated Learning via Compressed Model Perturbation
Y. Guo, R. Hu, and Y. Gong
IEEE Conference on Communications and Network Security (CNS), Austin, TX, USA, Oct. 3-5, 2022
Hybrid Local SGD for Federated Learning with Heterogeneous Communications
Y. Guo, Y. Sun, R. Hu, and Y. Gong
International Conference on Learning Representations (ICLR), Virtual, Apr. 25-29, 2022.
Energy-Efficient Distributed Machine Learning at Wireless Edge with Device-to-Device Communication
R. Hu, Y. Guo, and Y. Gong
IEEE Global Communications Conference (ICC), Seoul, South Korea, May 16-20, 2022.
Federated Learning with Sparsification-Amplified Privacy and Adaptive Optimization
R. Hu, Y. Gong, and Y. Guo
International Joint Conference on Artificial Intelligence (IJCAI), Montreal-themed Virtual Reality, Aug. 21-26, 2021.
Trading Data For Learning: Incentive Mechanism For On-Device Federated Learning
R. Hu and Y. Gong
IEEE Global Communications Conference (GLOBECOM), Taipei, Taiwan, Dec. 7-11, 2020.
Certified Robustness of Graph Classification against Topology Attack with Randomized Smoothing
Z. Gao, R. Hu, and Y. Gong
IEEE Global Communications Conference (GLOBECOM), Taipei, Taiwan, Dec. 7-11, 2020.
Privacy-Preserving Personalized Federated Learning
R. Hu, Y. Guo, H. Li, Q. Pei, Y. Gong
IEEE Global Communications Conference (ICC), Dublin, Ireland, June 7-11 2020.
Targeted Poisoning Attacks on Social Recommender Systems
R. Hu, Y. Guo, M. Pan, Y. Gong
IEEE Global Communications Conference (GLOBECOM), Waikoloa, HI, USA, Dec. 9-13, 2019.
Secret Dispersion: Secure Data Delivery in Cyber Physical System (poster)
R. Hu and Y. Gong
IEEE Conference on Communications and Network Security (CNS), Beijing, China, May 30 - June 1, 2018.
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