Welcome to Zikai's Homepage
 |
|
About Me [Google Scholar]
[Latest CV] (by Apr. 2026)
📢 I am actively seeking academic positions and welcome connections!
Research Interests: Federated Learning, Efficient AI, and Cybersecurity.
Education: PhD in Computer Science and Engineering at University of Nevada, Reno (2023-present)
What is New!
[04/2026] Excited to share that I received the Google Cloud Research Credits Program from Google for our Agentic AI project—big thanks to Google for the generous support!
[04/2026] Our work XMark: Reliable Multi-Bit Watermarking for LLM-Generated Texts was accepted by ACL 2026!
[03/2026] Excited to be invited by Flower Labs to be an early contributor to Flower Hub, which is designed to make federated applications easy to publish, discover, and run across heterogeneous environments without requiring users to manage infrastructure-level complexity. Check out tons of amazing federated learning apps!
[01/2026] Our work Heterogeneous Federated Fine-Tuning with Parallel One-Rank Adaptation was accepted by ICLR 2026! The code has been released!
[01/2026] Our work Traceable Black-Box Watermarks For Federated Learning was accepted by ICLR 2026!
[09/2025] Our paper FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models was accepted by NeurIPS 2025! Thanks Flower Labs for the amazing collaboration, check out the leaderboard and submit your solutions!
[09/2025] We are pleased to announce that On the Out-of-Distribution Backdoor Attack for Federated Learning has been accepted to ACM MobiHoc 2025! The code has been released!
[08/2025] Excited to share that our work Federated Learning for Smart Grid: A Survey on Applications and Potential Vulnerabilities was accepted at ACM TCPS 2025! The FedGridShield project has been released!
[08/2025] I received the HDRFS Student Publication & Travel Support from NSF EPSCoR, USA.
[06/2025] Thrilled to announce the acceptance of Fed-HeLLo: Efficient Federated Foundation Model Fine-Tuning with Heterogeneous LoRA Allocation at IEEE TNNLS 2025! The code has been released!
[02/2025] Our paper Detecting Backdoor Attacks in Federated Learning via Direction Alignment Inspection has been accepted for publication in CVPR 2025! The code has been released!
[10/2024] We are delighted that Achieving Byzantine-Resilient Federated Learning via Layer-Adaptive Sparsified Model Aggregation was accepted by WACV 2025! The code has been released!
[01/2024] I received the Nevada WateReuse Research Grant as Co-PI from WateReuse Association, USA.
[12/2023] I gave an invited talk at the Computational Modeling and Analysis Core Meet at UNR, USA.
[10/2023] I received the 2023 IEEE CNS Travel Grant from NSF, USA.
[10/2023] I won First Place Poster at the 2023 UNR Cybersecurity Conference, USA.
[08/2023] Our work Byzantine-robust Federated Learning with Variance Reduction and Differential Privacy has been accepted to IEEE CNS 2023! The code has been released!
[01/2023] I started my PhD program in the Department of Computer Science and Engineering at the University of Nevada, Reno, USA. 🎉
[07/2022] Our paper Global-local Feature Aggregation for Event-based Object Detection on Eventkitti was accepted by IEEE MFI 2022!
[10/2021] I received a Chinese patent: "Wheat Head Detection Method based on Computer Vision Semi-supervised Pseudo Label Learning" (CN113554627A).
[08/2021] I joined Tongji University (Shanghai, China) as a research assistant, working on multi-modality research projects.
[07/2021] Pleased to announce that DRNet: Towards Fast, Accurate and Practical Dish Recognition was accepted by Science China-Technological Sciences 2021!
[07/2021] I received a Chinese patent: "Low-power Consumption Real-time Helmet Detection Method based on Computer Vision Target Detection" (CN113128476A).
[05/2021] I joined DMAI (Guangzhou, China) as a research intern, focusing on AI research for education.
[02/2021] Excited to share that our paper Distractor-Aware Fast Tracking via Dynamic Convolutions and MOT Philosophy has been accepted at CVPR 2021! The code has been released!
[08/2020] I achieved TOP 1% (22/2245), Silver Medal in the Kaggle Global Wheat Detection Competition, Computer Vision Problems in Plant Phenotyping (CVPPP) Workshop, ECCV 2020, Online.
[10/2018] I received the Graduate Innovation Fund in Scientific Research from Huaqiao University, China.
Selected Publication
Preprints
► Zikai Zhang, Rui Hu, Ping Liu, and Jiahao Xu. Fed-pilot: Optimizing LoRA Allocation for Efficient Federated Fine-Tuning with Heterogeneous Clients. ArXiv. [pdf]
► Zikai Zhang, Rui Hu, Olivera Kotevska, and Jiahao Xu. SelfGrader: Stable Jailbreak Detection for Large Language Models using Token-Level Logits. ArXiv. [pdf]
► Zikai Zhang, Rui Hu, Olivera Kotevska, and Jiahao Xu. Vision Token Manipulation Attacks on Cloud-Edge Inference of Large Vision-Language Models. ArXiv.
2026
► [2026-04] Jiahao Xu, Rui Hu, Olivera Kotevska, and Zikai Zhang. XMark: Reliable Multi-Bit Watermarking for LLM-Generated Texts. The 64th Annual Meeting of the Association for Computational Linguistics, ACL (2026).
► [2026-01] Zikai Zhang, Rui Hu, and Jiahao Xu. Heterogeneous Federated Fine-Tuning with Parallel One-Rank Adaptation. The Fourteenth International Conference on Learning Representations, ICLR (2026). [pdf][code]
► [2026-01] Jiahao Xu, Rui Hu, Olivera Kotevska, Zikai Zhang. Traceable Black-Box Watermarks for Federated Learning. The Fourteenth International Conference on Learning Representations, ICLR (2026). [pdf]
2025
► [2025-09] Yan Gao, Massimo Roberto Scamarcia, Javier Fernandez-Marques, Mohammad Naseri, Chong Shen Ng, Dimitris Stripelis, Zexi Li, Tao Shen, Jiamu Bai, Daoyuan Chen, Zikai Zhang, Rui Hu, InSeo Song, Lee KangYoon, Hong Jia, Ting Dang, Junyan Wang, Zheyuan Liu, Daniel Janes Beutel, Lingjuan Lyu, and Nicholas D Lane. FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models. Advances in Neural Information Processing Systems, NeurIPS (2025). [pdf][Project]
► [2025-09] Jiahao Xu, Zikai Zhang, and Rui Hu. On the Out-of-Distribution Backdoor Attack for Federated Learning. The 26th International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, ACM MobiHoc (2025). [pdf][code]
► [2025-08] Zikai Zhang, Suman Rath, Jiahao Xu, and Tingsong Xiao. Federated Learning for Smart Grid: A Survey on Applications and Potential Vulnerabilities. ACM Transactions on Cyber-Physical Systems, ACM TCPS (2026). [pdf][code]
► [2025-06] Zikai Zhang, Ping Liu, Jiahao Xu, and Rui Hu. Fed-HeLLo: Efficient Federated Foundation Model Fine-Tuning with Heterogeneous LoRA Allocation. IEEE Transactions on Neural Networks and Learning Systems, IEEE TNNLS (2025). [pdf][code]
► [2025-02] Jiahao Xu, Zikai Zhang, and Rui Hu. Detecting Backdoor Attacks in Federated Learning via Direction Alignment Inspection. Proceedings of the Computer Vision and Pattern Recognition Conference, CVPR (2025). [pdf][code]
2024
► [2024-10] Jiahao Xu, Zikai Zhang, and Rui Hu. Achieving Byzantine-Resilient Federated Learning via Layer-Adaptive Sparsified Model Aggregation. IEEE/CVF Winter Conference on Applications of Computer Vision, WACV (2025). [pdf][code]
► [2024-10] Jiahao Xu, Zikai Zhang, and Rui Hu. Backdoored Model in Federated Learning via Individual Unlearning. IEEE/CVF Winter Conference on Applications of Computer Vision, WACV (2025).
2023
► [2023-08] Zikai Zhang, and Rui Hu. Byzantine-robust Federated Learning with Variance Reduction and Differential Privacy. 2023 IEEE Conference on Communications and Network Security, IEEE CNS (2023). [pdf][code]
2022
► [2022-07] Zichen Liang, Hu Cao, Chu Yang, Zikai Zhang, and Guang Chen. Global-local Feature Aggregation for Event-based Object Detection on Eventkitti. 2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, IEEE MFI (2022).
2021
► [2021-07] Siyuan Cheng, Binfei Chu, Bineng Zhong, Zikai Zhang, Xin Liu, Zhenjun Tang, and Xianxian Li. DRNet: Towards Fast, Accurate and Practical Dish Recognition. Science China-Technological Sciences (2021). [pdf]
► [2021-02] Zikai Zhang, Bineng Zhong, Shengping Zhang, Zhenjun Tang, Xin Liu, and Zhaoxiang Zhang. Distractor-Aware Fast Tracking via Dynamic Convolutions and MOT Philosophy. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR (2021). [pdf][code]
Preprints
2026
2025
2024
2023
2022
2021
Award and Grant
► Apr. 2026 PI, Google Cloud Research Credits Program, Google, USA.
► Mar. 2026 Early Contributor Badge for Invited Contributors, Flower Labs, Online.
► Oct. 2025 First Place Poster, 2025 UNR Cybersecurity Conference, USA.
► Sep. 2025 Co-PI, Dynamic Language Infrastructure (DLI), NSF, USA (Under Review).
► Aug. 2025 HDRFS Student Publication & Travel Support, NSF EPSCoR, USA.
► Oct. 2024 First Place Poster, 2024 UNR Cybersecurity Conference, USA.
► Jan. 2024 Co-PI, Nevada WateReuse Research Grant, WateReuse Association, USA.
► Oct. 2023 2023 IEEE CNS Travel Grant, NSF, USA.
► Oct. 2023 First Place Poster, 2023 UNR Cybersecurity Conference, USA.
► Oct. 2020 TOP 1% (5/489), Electric Vehicle Helmet Recognition Competition, The 3rd Chinese Conference on Pattern Recognition and Computer Vision (PRCV 2020), China.
► Aug. 2020 TOP 1% (22/2245), Silver Medal, Kaggle Global Wheat Detection Competition, Computer Vision Problems in Plant Phenotyping (CVPPP) Workshop, 2020 European Conference on Computer Vision (ECCV), Online.
► 2018-2021 Sole PI, Graduate Innovation Fund in Scientific Research, Huaqiao University, China.
Professional Service
TPC/PC Member:
The Annual AAAI Conference on Artificial Intelligence (AAAI) 2025, 2026; International Conference on Smart Mechatronics (ICSMech) 2024
Journal Reviewer:
IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Dependable and Secure Computing, IEEE/ACM Transactions on Networking, Information Processing and Management, IEEE Open Journal of the Communications Society, China Communication, Scientific Reports, npj Artificial Intelligence, Journal of Information Security and Applications, IEEE Latin America Transactions, Cluster Computing, The Journal of Supercomputing, Journal of Real-Time Image Processing, Engineering, Technology & Applied Science Research, International Journal of Machine Learning and Cybernetics
Conference Reviewer:
ICLR 2026, ICML 2025, 2026, NeurIPS 2022, 2024, 2025, 2026 CVPR 2025, 2026, ICCV 2025, ECCV 2026, COLM 2026, WACV 2025, ICPR 2025, CCNC 2024, 2025, ICCCN 2025, FedVision 2026
Mentoring & Teaching
Mentoring:
► 2025 Fall Mentor, Research Project, University of Nevada, Reno, USA.
Students: Mia Fisher, Karam Alkherej
Project: Implicit Prompt Injection Attack and Defense
► 2023-2024 Mentor, Capstone Project for Undergraduates, University of Nevada, Reno, USA.
Students: Cody Long, Zachary Strazi, Kristian Konstantinov, Jacob Ayers
Project: Automatic Speech Recognition Attack with Adversarial Examples
► 2023 Summer Mentor, Research Experiences for Undergraduates (REU), University of Nevada, Reno, USA.
Students: Manny Ortiz (Penn State University), Zhang Lin (Colorado School of Mines)
Project: Backdoor Attacks in Federated Learning Systems
Supported by NSF #2150394
Teaching:
► 2025 Fall Graduate Teaching Assistant, CS442/642 Cloud Computing, University of Nevada, Reno, USA.
► 2025 Spring Graduate Teaching Assistant, CS302 Data Structures, University of Nevada, Reno, USA.
► 2019-2020 Sessional Lecturer, Web Interaction Design, Xiamen Institute of Technology, China.
Students: Mia Fisher, Karam Alkherej
Project: Implicit Prompt Injection Attack and Defense
Students: Cody Long, Zachary Strazi, Kristian Konstantinov, Jacob Ayers
Project: Automatic Speech Recognition Attack with Adversarial Examples
Students: Manny Ortiz (Penn State University), Zhang Lin (Colorado School of Mines)
Project: Backdoor Attacks in Federated Learning Systems
Supported by NSF #2150394