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TsingZ0/README.md

Biography

Pursue what truly interests you in life. –––Jianqing Zhang

I am Jianqing (Tsing) Zhang, a second-year PhD student in Computer Science, co-supervised by Yang Liu at Tsinghua University and Jian Cao at Shanghai Jiao Tong University. I completed my Master's degree at Shanghai Jiao Tong University in 2023, where I had the privilege of working with Ruhui Ma, Tao Song, Yang Hua (Queen's University Belfast), and Hao Wang (Stevens Institute of Technology). I earned my Bachelor's degree at Hangzhou Dianzi University in 2020, and was fortunate to work with Dongjin Yu and Dongjing Wang.

My research interests include Synthetic Data Generation, Large and Small Models Collaboration, and Federated Learning. Please see slides for a summary. Additionally, I am a passionate photographer, always seeking to capture the beauty of the world through my lens.

I firmly believe that collaboration—a core principle of Federated Learning—is essential for advancing scientific research. I am always eager to collaborate with passionate and like-minded partners.

Internships

  • ByteDance | Machine Learning Platform - Security and Trust | Contributor to the open-source project FedLearner

Open-source Software

  • 🎉[PFLlib (1K+ stars)] Personalized Federated Learning Algorithm Library. [paper] [code]
    • Jianqing Zhang, Yang Liu, Yang Hua, Hao Wang, Tao Song, Zhengui Xue, Ruhui Ma, Jian Cao
  • 🎉[HtFLlib] Heterogeneous Federated Learning Algorithm Library. [code]
  • 🎉[FL-IoT] Federated Learning Algorithms in IoT Environments. [code]

Featured Publications (Google Scholar)

Stage Ⅳ (Large Models): Synthetic Data Generation

  • 🎉[EMNLP'24] FuseGen: PLM Fusion for Data-Generation Based Zero-Shot Learning. [paper] [code]
    • Tianyuan Zou, Yang Liu, Peng Li, Jianqing Zhang, Jingjing Liu, Ya-Qin Zhang

Stage Ⅲ (Large and Small Models): Large and Small Models Collaboration

  • 🎉[CVPR'24] An Upload-Efficient Scheme for Transferring Knowledge From a Server-Side Pre-trained Generator to Clients in Heterogeneous Federated Learning. [paper] [code]
    • Jianqing Zhang, Yang Liu, Yang Hua, Jian Cao

Stage Ⅱ (Small Models): Heterogeneous Federated Learning

  • FedL2G: Learning to Guide Local Training in Heterogeneous Federated Learning. [paper] [code]
    • Jianqing Zhang, Yang Liu, Yang Hua, Jian Cao, Qiang Yang
  • 🎉[CVPR'24] An Upload-Efficient Scheme for Transferring Knowledge From a Server-Side Pre-trained Generator to Clients in Heterogeneous Federated Learning. [paper] [code]
    • Jianqing Zhang, Yang Liu, Yang Hua, Jian Cao
  • 🎉[AAAI'24] FedTGP: Trainable Global Prototypes with Adaptive-Margin-Enhanced Contrastive Learning for Data and Model Heterogeneity in Federated Learning. [paper] [code]
    • Jianqing Zhang, Yang Liu, Yang Hua, Jian Cao

Stage Ⅰ (Small Models): Personalized Federated Learning

  • 🎉[NeurIPS'23] Eliminating Domain Bias for Federated Learning in Representation Space. [paper] [code]
    • Jianqing Zhang, Yang Hua, Jian Cao, Hao Wang, Tao Song, Zhengui Xue, Ruhui Ma, Haibing Guan
  • 🎉[ICCV'23] GPFL: Simultaneously Learning Generic and Personalized Feature Information for Personalized Federated Learning. [paper] [code]
    • Jianqing Zhang, Yang Hua, Hao Wang, Tao Song, Zhengui Xue, Ruhui Ma, Jian Cao, Haibing Guan
  • 🎉[KDD'23] FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policy. [paper] [code]
    • Jianqing Zhang, Yang Hua, Hao Wang, Tao Song, Zhengui Xue, Ruhui Ma, Haibing Guan
  • 🎉[AAAI'23] FedALA: Adaptive Local Aggregation for Personalized Federated Learning. [paper] [code]
    • Jianqing Zhang, Yang Hua, Hao Wang, Tao Song, Zhengui Xue, Ruhui Ma, Haibing Guan

Other Work

  • 🎉[IEEE Transactions on Cognitive and Developmental Systems] pFedEff: An Efficient and Personalized Federated Cognitive Learning Framework in Multi-agent Systems. [paper]
    • Hongjian Shi, Jianqing Zhang, Shuming Fan, Ruhui Ma, Haibing Guan
  • 🎉[Neurocomputing] TLSAN: Time-aware long-and short-term attention network for next-item recommendation. [paper] [code]
    • Jianqing Zhang, Dongjing Wang, Dongjin Yu

Photography

My photography gallery can be found at: https://tsing.tuchong.com/work/

  • 🎉[2022] International Photography Award (IPA) Official Selection
  • 🎉[2020] Top 30 in the Metro Yunchuang Photo Competition

Pinned Loading

  1. PFLlib PFLlib Public

    37 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 20 datasets.

    Python 1.5k 307

  2. HtFLlib HtFLlib Public

    You only need to configure one file to support model heterogeneity. Consistent GPU memory usage for single or multiple clients.

    Python 110 5

  3. FedL2G FedL2G Public

    FedL2G: Learning to Guide Local Training in Heterogeneous Federated Learning

    Python 5

  4. FedKTL FedKTL Public

    CVPR 2024 accepted paper, An Upload-Efficient Scheme for Transferring Knowledge From a Server-Side Pre-trained Generator to Clients in Heterogeneous Federated Learning

    Python 39 3

  5. FedTGP FedTGP Public

    AAAI 2024 accepted paper, FedTGP: Trainable Global Prototypes with Adaptive-Margin-Enhanced Contrastive Learning for Data and Model Heterogeneity in Federated Learning

    Python 38 4

  6. DBE DBE Public

    NeurIPS 2023 accepted paper, Eliminating Domain Bias for Federated Learning in Representation Space

    Python 21 1