Publications

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(Selected) Publication by Research Topic

GenAI: Text-to-Motion | Image and Video Generation and Editing | 3D Generation and Editing
Video Understanding: Grounding and Reasoning | Human Pose/Mesh Analysis | Human Action Recognition | Anomaly Detection
Other Computer Vision Tasks: Object Detection | Image Segmentation
Medical Image Computing & Healthcare Applications: Medical Image Segmentation | Medical Foundation Models and Datasets | Healthcare Applications
Image and Video Processing: Image Restoration (Denoising, SR, etc.)
Geospatial Analysis and Remote Sensing: Image Geolocalization | Remote Sensing
Machine Learning: Federated Learning | Unsupervised, Self- and Semi-supervised Learning | Multimodal Learning | Efficiency

Go to Publications by Year

Federated Learning

Mixture of Experts Made Personalized: Federated Prompt Learning for Vision-Language Models
Jun Luo, Chen Chen, Shandong Wu
International Conference on Learning Representations (ICLR), 2025
[Paper]

Navigating Heterogeneity and Privacy in One-Shot Federated Learning with Diffusion Models
Matias Mendieta, Guangyu Sun, and Chen Chen
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025
[Paper] [Code]

Exploring Parameter-Efficient Fine-Tuning to Enable Foundation Models in Federated Learning
Guangyu Sun, Umar Khalid, Matias Mendieta, Pu Wang, Chen Chen
IEEE International Conference on Big Data (BigData), 2024
[Paper] [Code]

Federated Learning Client Pruning for Noisy Labels
Mahdi Morafah, Hojin Chang, Chen Chen, Bill Lin
ACM Transactions on Modeling and Performance Evaluation of Computing Systems, 2024
[Paper] [Code]

Towards Diverse Device Heterogeneous Federated Learning via Task Arithmetic Knowledge Integration
Mahdi Morafah, Vyacheslav Kungurtsev, Hojin Matthew Chang, Chen Chen, Bill Lin
Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS), 2024
[Paper] [Project Website] [Code]

Taming Cross-Domain Representation Variance in Federated Prototype Learning with Heterogeneous Data Domains
Lei Wang, Jieming Bian, Letian Zhang, Chen Chen, Jie Xu
Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS), 2024
[Paper] [Code]

Towards Multi-modal Transformers in Federated Learning
Guangyu Sun, Matias Mendieta, Aritra Dutta, Xin Li, and Chen Chen
European Conference on Computer Vision (ECCV), 2024
[Paper] [Code]

Rethinking Data Heterogeneity in Federated Learning: Introducing a New Notion and Standard Benchmarks
Saeed Vahidian, Mahdi Morafah, Chen Chen, Mubarak Shah, Bill Lin
IEEE Transactions on Artificial Intelligence (TAI), 2023
[Paper] [Code]

FedPerfix: Towards Partial Model Personalization of Vision Transformers in Federated Learning
Guangyu Sun, Matias Mendieta, Jun Luo, Shandong Wu, Chen Chen
IEEE/CVF International Conference on Computer Vision (ICCV), 2023
[Paper] [Code]

When Do Curricula Work in Federated Learning?
Saeed Vahidian, Sreevatsank Kadaveru, Woonjoon Baek, Weijia Wang, Vyacheslav Kungurtsev, Chen Chen, Mubarak Shah, Bill Lin
IEEE/CVF International Conference on Computer Vision (ICCV), 2023
[Paper]

PGFed: Personalize Each Client’s Global Objective for Federated Learning
Jun Luo, Matias Mendieta, Chen Chen, Shandong Wu
IEEE/CVF International Conference on Computer Vision (ICCV), 2023
[Paper] [Code]

CEFHRI: A Communication Efficient Federated Learning Framework for Recognizing Industrial Human-Robot Interaction
Umar Khalid, Hasan Iqbal, Saeed Vahidian, Jing Hua, Chen Chen
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023
[Paper] [Code]

DHA-FL: Enabling Efficient and Effective AIoT via Decentralized Hierarchical Asynchronous Federated Learning
Wesley Houston Huff, pinyarash pinyoanuntapong, Ravikumar Balakrishnan, Hao Feng, Minwoo Lee, Pu Wang, Chen Chen
MLSys 2023 Workshop on Resource-Constrained Learning in Wireless Networks, 2023
[Paper]

Efficient Distribution Similarity Identification in Clustered Federated Learning via Principal Angles Between Client Data Subspaces
Saeed Vahidian, Mahdi Morafah, Weijia Wang, Vyacheslav Kungurtsev, Chen Chen, Mubarak Shah, Bill Lin
AAAI Conference on Artificial Intelligence (AAAI), 2023 (Acceptance Rate = 19.6%)
[Paper] [Code]

EdgeML: Towards Network-Accelerated Federated Learning over Wireless Edge
Pinyarash Pinyoanuntapong, Prabhu Janakaraj, Ravikumar Balakrishnan, Minwoo Lee, Chen Chen, Pu Wang
Computer Networks, 2022
[Paper]

Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning
Matias Mendieta, Taojiannan Yang, Pu Wang, Minwoo Lee, Zhengming Ding, Chen Chen
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022 (Oral)
[Paper] [Code] [Best Paper Nominee (33 out of 8,161), Image]

Towards Scalable and Robust AIoT via Decentralized Federated Learning
Pinyarash Pinyoanuntapong, Wesley Houston Huff, Minwoo Lee, Chen Chen, and Pu Wang
IEEE Internet of Things Magazine, 2022
[Paper]

Sim-to-Real Transfer in Multi-agent Reinforcement Networking for Federated Edge Computing
Pinyarash Pinyoanuntapong, Tagore Pothuneedi, Ravikumar Balakrishnan, Minwoo Lee, Chen Chen, Pu Wang
ACM/IEEE 6th Symposium on Edge Computing (SEC), 2021
[Paper]

FedAir: Towards Multi-hop Federated Learning Over-the-Air
Pinyarash Pinyoanuntapong, Prabhu Janakaraj, Pu Wang, Minwoo Lee, Chen Chen
IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2020
[Paper]