Jie ZHANG (张婕)

Postdoctoral Fellow

Department of Computing (COMP)
Faculty of Engineering
The Hong Kong Polytechnic University

Office:VA 322, Shaw Amenities Building, PolyU, Kowloon, Hong Kong SAR.
Email:[jie-comp.zhang AT polyu.edu.hk]
Google Scholar

Short Bio

Jie ZHANG is currently a Post-doctoral Fellow in the Department of Computing at Hong Kong Polytechnic University (香港理工大学), Hong Kong SAR, China, where she received her Ph.D. degree in 2022, supervised by Prof. Song Guo, Fellow of IEEE. Before that, she received the B.E. and M.E. degree from China University of Geosciences (中国地质大学), Wuhan, China, supervised by Prof. Deze Zeng.

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.

Working Experience

Post-doctoral Fellow: The Hong Kong Polytechnic University, Oct. 2022 - Now
Supervisor: Prof. Song Guo, IEEE Fellow.

Education Background

Ph.D.: The Hong Kong Polytechnic University, Jan. 2019 - Sep. 2022
Supervisor: Prof. Song Guo, IEEE Fellow.
M.E.: China University of Geosciences, Sep. 2015 - Jun. 2018
Supervisor: Prof. Deze Zeng.
B.E.: China University of Geosciences, Sep. 2011 - Jun. 2015
Supervisor: Prof. Junqin Fan.

Publications

Conference Papers

(Note: "*" indicates equal contribution (co-first authors),"†" marks the corresponding authors.)

[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).

Journal Papers

[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).

Teaching Experience

Teaching Assistant, Programming Fundamentals, PolyU, Spring 2019, Autumn 2019.
Teaching Assistant, Big Data Analytics, PolyU, Spring 2020, Spring 2021.
Teaching Assistant, Big Data Computing, PolyU, Autumn 2020, Autumn 2021.

Academic Service

PC Member / Journal Reviewer

Reviewer for The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR)
Reviewer for Conference on Neural Information Processing Systems (NeurIPS)
Reviewer for The International Conference on Machine Learning (ICML)
Reviewer for IEEE Transactions on Parallel and Distributed Systems (IEEE TPDS)
Reviewer for IEEE Transactions on Mobile Computing (IEEE TMC)
Reviewer for IEEE Transactions on Computers (IEEE TC)

Selected Honors

2nd Prize, CUMCM (Contemporary Undergraduate Mathematical Contest in Modeling).
Awarded by CSIAM (China Society for Industrial and Applied Mathematics), Jun 2013.
National Encouragement Scholarship.
Awarded by China University of Geoscience, June 2014.
Outstanding Undergraduate Student Honor.
Awarded by China University of Geoscience, June 2015.
1st Prize, Science and Technology Paper Seminar.
Awarded by China University of Geoscience, June 2017.