Hao Zheng

About Me

Hello! I’m Hao Zheng, a Postdoctoral Researcher at Sun Yat-sen University, supervised by Prof. Wenqi Ren. Previously, I was a Ph.D. student in the School of Computer Science and Engineering at Central South University, advised by Prof. Zhigang Hu. I also conducted visiting research at Western University under the guidance of Prof. Boyu Wang and Prof. Charles Ling. My research interests include Optimization for Personalized Federated Learning, as well as Deep Learning and Computer Vision in Remote Sensing.

Before that, I received my M.S. degree from Central South University in 2021 and my B.S. degree from Taiyuan University of Technology in 2018.

I’m looking for motivated collaborators to turn ideas into papers. Whether you are an undergraduate, master’s, or Ph.D. student, you are welcome to email me—let’s explore federated learning, remote sensing vision, and interdisciplinary ML problems together.

Recent Activities

Nov 08, 2025	Our three papers, “HiFC-GAN: Hierarchical Feature-Constrained GAN for Optical-to-SAR Transfer in SAR Target Classification (Poster)” ,”Intra-Class Unbiased Prototype Aggregation and Classifier Collaboration for Personalized Federated Learning (Poster)” and “Graph Domain Adaptation via Homophily-Agnostic Reconstructing Structure (Oral)” are accepted at AAAI 2026.
Sep 19, 2025	Our paper, “Versatile Transferable Unlearnable Example Generator”, was accepted at NeurIPS 2025.
Jun 11, 2025	Our paper, “Proactive Spatio-Temporal Request Prediction for Replica Placement in Edge-Cloud Computing”, was accepted at IoTJ.
May 19, 2025	Honored to be recognized by ICLR 2025 as a notable reviewer.
Mar 20, 2025	Our two papers, “ElimPCL: Eliminating Noise Accumulation with Progressive Curriculum Labeling for Source-Free Domain Adaptation” and “PCM-SAR: Physics-Driven Contrastive Mutual Learning for SAR Classification” are accepted at ICME 2025.
Feb 26, 2025	Our paper, “FedCALM: Conflict-aware Layer-wise Mitigation for Selective Aggregation in Deeper Personalized Federated Learning”, was accepted at CVPR 2025.
Dec 23, 2024	Our paper, “ConFREE: Conflict-free Client Update Aggregation for Personalized Federated Learning”, was accepted at AAAI 2025 (oral, acceptance rate ≈ 4.6%).
Dec 20, 2024	Our paper, “GradPFL: Gradient-Driven Adaptive Clustering in Personalized Federated Learning”, was accepted at ICASSP 2025.

Selected Publications

(Note: * indicates equal contribution.)

AAAI2026

HiFC-GAN: Hierarchical Feature-Constrained GAN for Optical-to-SAR Transfer in SAR Target Classification

Hao Zheng, Zhigang Hu, Meiguang Zheng, Liu Yang, Aikun Xu, Tingxuan Chen, Rongchang Zhao, and Boyu Wang

In Proceedings of the AAAI Conference on Artificial Intelligence, 2026

Bib

@inproceedings{zheng2026hifcgan,
  title = {HiFC-GAN: Hierarchical Feature-Constrained GAN for Optical-to-SAR Transfer in SAR Target Classification},
  author = {Zheng, Hao and Hu, Zhigang and Zheng, Meiguang and Yang, Liu and Xu, Aikun and Chen, Tingxuan and Zhao, Rongchang and Wang, Boyu},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  year = {2026},
}

AAAI2026

Intra-Class Unbiased Prototype Aggregation and Classifier Collaboration for Personalized Federated Learning

Hao Zheng, Shiyu Song, Zhigang Hu, Meiguang Zheng, Liu Yang, Aikun Xu, Rongchang Zhao, Ruizhi Pu, Ruiyi Fang, and Boyu Wang

In Proceedings of the AAAI Conference on Artificial Intelligence, 2026

Bib

@inproceedings{zheng2026fedic,
  title = {Intra-Class Unbiased Prototype Aggregation and Classifier Collaboration for Personalized Federated Learning},
  author = {Zheng, Hao and Song, Shiyu and Hu, Zhigang and Zheng, Meiguang and Yang, Liu and Xu, Aikun and Zhao, Rongchang and Pu, Ruizhi and Fang, Ruiyi and Wang, Boyu},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  year = {2026},
}

CVPR2025

FedCALM: Conflict-aware Layer-wise Mitigation for Selective Aggregation in Deeper Personalized Federated Learning

Hao Zheng, Zhigang Hu, Liu Yang, Meiguang Zheng, Aikun Xu, and Boyu Wang

In Proceedings of the Computer Vision and Pattern Recognition Conference, 2025

Bib

@inproceedings{zheng2025fedcalm,
  title = {FedCALM: Conflict-aware Layer-wise Mitigation for Selective Aggregation in Deeper Personalized Federated Learning},
  author = {Zheng, Hao and Hu, Zhigang and Yang, Liu and Zheng, Meiguang and Xu, Aikun and Wang, Boyu},
  booktitle = {Proceedings of the Computer Vision and Pattern Recognition Conference},
  pages = {15444--15453},
  year = {2025},
}

AAAI2025

ConFREE: Conflict-free Client Update Aggregation for Personalized Federated Learning

Hao Zheng, Zhigang Hu, Liu Yang, Meiguang Zheng, Aikun Xu, and Boyu Wang

In Proceedings of the AAAI Conference on Artificial Intelligence, 2025, (Oral, Acceptance rate ≈ 4.6%)

Bib Code Poster

@inproceedings{zheng2025confree,
  title = {ConFREE: Conflict-free Client Update Aggregation for Personalized Federated Learning},
  author = {Zheng, Hao and Hu, Zhigang and Yang, Liu and Zheng, Meiguang and Xu, Aikun and Wang, Boyu},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  volume = {39},
  number = {21},
  pages = {22875--22883},
  year = {2025},
}

IoTJ

Proactive Spatio-Temporal Request Prediction for Replica Placement in Edge-Cloud Computing

Hao Zheng, Zhigang Hu, Liu Yang, Aikun Xu, Meiguang Zheng, Hui Xiao, and Keqin Li

IEEE Internet of Things Journal, 2025

Bib

@article{zheng2025proactive,
  title = {Proactive Spatio-Temporal Request Prediction for Replica Placement in Edge-Cloud Computing},
  author = {Zheng, Hao and Hu, Zhigang and Yang, Liu and Xu, Aikun and Zheng, Meiguang and Xiao, Hui and Li, Keqin},
  journal = {IEEE Internet of Things Journal},
  year = {2025},
  publisher = {IEEE},
}

TGRS

Multi-Feature Collaborative Fusion Network with Deep Supervision for Sar Ship Classification

Hao Zheng, Zhigang Hu, Liu Yang, Aikun Xu, Meiguang Zheng, Ce Zhang, and Keqin Li

IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2023

Bib Code

@article{zheng2023multi,
  title = {Multi-Feature Collaborative Fusion Network with Deep Supervision for Sar Ship Classification},
  author = {Zheng, Hao and Hu, Zhigang and Yang, Liu and Xu, Aikun and Zheng, Meiguang and Zhang, Ce and Li, Keqin},
  journal = {IEEE Transactions on Geoscience and Remote Sensing (TGRS)},
  year = {2023},
  publisher = {IEEE},
}

GRSL

MetaBoost: A Novel Heterogeneous DCNNs Ensemble Network with Two-Stage Filtration for SAR Ship Classification

Hao Zheng, Zhigang Hu, Jianjun Liu, Yuhang Huang, and Meiguang Zheng

IEEE Geoscience and Remote Sensing Letters (GRSL), 2022

Bib

@article{zheng2022metaboost,
  title = {MetaBoost: A Novel Heterogeneous DCNNs Ensemble Network with Two-Stage Filtration for SAR Ship Classification},
  author = {Zheng, Hao and Hu, Zhigang and Liu, Jianjun and Huang, Yuhang and Zheng, Meiguang},
  journal = {IEEE Geoscience and Remote Sensing Letters (GRSL)},
  volume = {19},
  pages = {1--5},
  year = {2022},
  publisher = {IEEE},
}

IPDPS2023

PFedSA: Personalized Federated Multi-Task Learning via Similarity Awareness

Chuyao Ye^*, Hao Zheng^*, Zhigang Hu, and Meiguang Zheng

In 2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2023, (Oral)

Bib

@inproceedings{ye2023pfedsa,
  title = {PFedSA: Personalized Federated Multi-Task Learning via Similarity Awareness},
  author = {Ye, Chuyao and Zheng, Hao and Hu, Zhigang and Zheng, Meiguang},
  booktitle = {2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS)},
  pages = {480--488},
  year = {2023},
  organization = {IEEE},
}