Research Assistant Professor
Office:3543, Academic Building, HKUST
Email:[csejzhang AT ust.hk]
Google Scholar
Jie ZHANG is currently a Research Assistant Professor in the Department of Computer Science and Engineering (CSE) at the Hong Kong University of Science and Technology (HKUST) , Hong Kong SAR, China. She obtained her Ph.D. degree from the Department of Computing, Hong Kong Polytechnic University in 2022, under the supervision of Prof. Song Guo, Fellow of IEEE. Prior to that, she obtained her B.E. and M.E. degree from China University of Geosciences, Wuhan, China.
Her research interest broadly lies in the areas of edge computing, federated learning, distributed AI systems and foundation models. Some specific topics such as heterogeneous training, personalization for federated learning, and inference acceleration for pre-trained large models are highly involved.
(Note: "*" indicates equal contribution (co-first authors),"†" marks the corresponding authors.)
[ICML] 
Easing Concept Bleeding in Diffusion via Entity Localization and Anchoring,
Jiewei Zhang, Song Guo, Peiran Dong, Jie Zhang, Ziming Liu, Yue Yu, and Xiaoming Wu.
in International Conference on Machine Learning (ICML'24), 2024.
(CCF-A).
[ICML] 
Causally Motivated Personalized Federated Invariant Learning with Shortcut-Averse Information-Theoretic Regularization,
Xueyang Tang, Song Guo, Jingcai Guo, Jie Zhang† and Yue Yu.
in International Conference on Machine Learning (ICML'24), 2024.
(CCF-A).
[ICML] 
Amend to Alignment: Decoupled Prompt Tuning for Mitigating Spurious Correlation in Vision-Language Models,
Jie Zhang, Xiaosong Ma, Song Guo, Peng Li, Wenchao Xu, Xueyang Tang and Zicong Hong.
in International Conference on Machine Learning (ICML'24), 2024.
(CCF-A).
[ICLR] 
Learning Personalized Causally Invariant Representations for Heterogeneous Federated Clients,
Xueyang Tang, Song Guo†, Jie Zhang†, Jingcai Guo.
in The Twelfth International Conference on Learning Representations (ICLR'24), 2024.
(CCF-A).
[CVPR] 
DiPrompT: Disentangled Prompt Tuning for Multiple Latent Domain Generalization in Federated Learning,
Sikai Bai*, Jie Zhang*, Song Guo, Shuaicheng Li, Jingcai Guo, Jun Hou, Tao Han, Xiaocheng Lu.
in The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR'24), 2024.
(CCF-A).
[AAAI] 
Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators,
Sikai Bai, Shuaicheng Li, Weiming Zhuang, Jie Zhang†, Kunlin Yang, Jun Hou, Shuai Yi, shuai zhang and Junyu Gao.
in Annual AAAI Conference on Artificial Intelligence (AAAI'24), 2024.
(CCF-A).
[NeurIPS] 
SwapPrompt: Test-Time Prompt Adaptation for Vision-Language Models,
Xiaosong Ma, Jie Zhang†, Song Guo, Wenchao Xu.
in Advances in Neural Information Processing Systems (NeurIPS'23), 2023.
(CCF-A).
[ICML] 
Towards Unbiased Training in Federated Open-world Semi-supervised Learning,
Jie Zhang, Xiaosong Ma, Song Guo and Wenchao Xu.
in International Conference on Machine Learning (ICML'23), 2023.
(CCF-A).
[CVPR] 
Layer-wised Model Aggregation for Personalized Federated Learning,
Xiaosong Ma*, Jie Zhang*, Song Guo and Wenchao Xu.
in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR'22), 2022.
(CCF-A).
[NeurIPS] 
Parameterized Knowledge Transfer for Personalized Federated Learning,
Jie Zhang, Song Guo, Xiaosong Ma, Haozhao Wang, Wenchao Xu, and Feijie Wu.
in Advances in Neural Information Processing Systems (NeurIPS'21), 2021.
(CCF-A).
[MM] 
Dual-view Attention Networks for Single Image Super-Resolution,
Jingcai Guo, Shiheng Ma, Jie Zhang, Qihua Zhou and Song Guo.
in 28th ACM International Conference on Multimedia (MM'20), 2020.
(CCF-A).
[ICPADS] 
Multi-Path Routing Oriented Flow Statistics Collection in Software Defined Networks,
Jie Zhang, Song Guo, Deze Zeng, and Zhihao Qu.
in IEEE International Conference on Parallel and Distributed Systems (ICPADS'19), 2019.
(CCF-C).
[SECON] 
Stochastic scheduling towards cost efficient network function virtualization in edge cloud,
Deze Zeng, Jie Zhang, Lin Gu and Song Guo.
in Annual IEEE International Conference on Sensing, Communication, and Networking (SECON), 2018.
(CCF-B).
[GLOBECOM] 
Joint optimization of virtual function migration and rule update in software defined NFV networks,
Jie Zhang, Deze Zeng, Lin Gu, Hong Yao, and Muzhou Xiong.
in IEEE Global Communications Conference (GLOBECOM'17), 2017.
(CCF-C).
[GLOBECOM] 
Minimize Coflow Completion Time via Join Optimization of Flow Scheduling and Processor Placement,
Deze Zeng, Jie Zhang, Lin Gu, Peng Li and Hong Yao.
in IEEE Global Communications Conference (GLOBECOM'17), 2017.
(CCF-C).
[CollaborateCom] 
On rule placement for multi-path routing in software-defined networks,
Jie Zhang, Deze Zeng, Lin Gu, Hong Yao, and Yuanyuan Fan.
in International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom'15), 2015.
(CCF-C).
[IEEE Network] 
Human Cognition Modeling for the Metaverse-oriented Design System,
Yan Hong, Song Guo, Xianyi Zeng, Jie Zhang†.
IEEE Network, 2024.
(SCI, JCR Q1).
[TC] 
Towards Data-independent Knowledge Transfer in Model-heterogeneous Federated Learning,
Jie Zhang, Song Guo, Jing Guo, Deze Zeng, Jingren Zhou and Albert Zomaya.
IEEE Transactions on Computers (TC), 2023.
(CCF-A).
[TPDS] 
Adaptive Vertical Federated Learning on Unbalanced Features,
Jie Zhang, Song Guo, Zhihao Qu, Deze Zeng, Haozhao Wang and Albert Zomaya.
IEEE Transactions on Parallel and Distributed Systems (TPDS), 2022.
(CCF-A).
[TC] 
Adaptive federated learning on Non-IID data with resource constraint,
Jie Zhang, Song Guo, Zhihao Qu, Deze Zeng, Yufeng Zhan, Qifeng Liu, and Rajendra Akerkar.
IEEE Transactions on Computers (TC), 2021.
(CCF-A).
[CSUR] 
Edge learning: The enabling technology for distributed big data analytics in the edge.,
Jie Zhang, Zhihao Qu, Chen Chen, Haozhao Wang, Yufeng Zhan, Baoliu Ye, and Song Guo.
ACM Computing Surveys (CSUR), 2021.
(SCI, JCR Q1).
[TETC] 
A survey of incentive mechanism design for federated learning,
Yufeng Zhan, Jie Zhang, Zicong Hong, Leijie Wu, Peng Li, and Song Guo.
IEEE Transactions on Emerging Topics in Computing (TETC), 2021.
(SCI, JCR Q1).
[TVT] 
Energy-efficient coordinated multipoint scheduling in green cloud radio access network,
Deze Zeng, Jie Zhang, Lin Gu, Song Guo, and Jiangtao Luo.
IEEE Transactions on Vehicular Technology (TVT), 2019.
(SCI, JCR Q1).
[IEEE Network] 
Take renewable energy into CRAN toward green wireless access networks,
Deze Zeng, Jie Zhang, Song Guo, Lin Gu, and Kun Wang.
IEEE Network, 2017.
(SCI, JCR Q1).