FLAIR-Community.github.io/index.html at main · FLAIR-Community/FLAIR-Community.github.io · GitHub

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<!DOCTYPE html>
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    <title>FLAIR</title>
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<header>
    <img src="https://raw.githubusercontent.com/FLAIR-Community/FLAIR-Community.github.io/main/.assets/logo.png" alt="Organization Logo">
    <h1>FLAIR Lab</h1>
</header>

<div class="container">
    <div class="section">
        <h2>About Us</h2>
        <p>Welcome to the Federated Learning and AI Research (FLAIR) lab. We are located at Beihang University and focus on cutting-edge AI research, especially in the field of federated learning. Our team is composed of leading experts and dedicated researchers who strive to advance knowledge and innovation in AI technologies.</p>
        <p>Our mission is to foster collaboration, drive impactful research, and develop practical applications that benefit both academia and industry. We believe in the power of open science and are committed to sharing our findings and tools with the broader community.</p>
        <p><strong>Location:</strong> Beihang University, Beijing, China</p>
        <p><strong>Contact:</strong> <a href="mailto:liu_xuefeng@buaa.edu.cn">liu_xuefeng@buaa.edu.cn</a></p>
    </div>

    <div class="section">
        <h2>Open Source Repositories</h2>
        <ul>
            <li><a href="https://github.com/FLAIR-Community/Fling" target="_blank">Fling</a> - A high-efficiency framework for federated learning incorporating various datasets and algorithms.</li>
        </ul>
    </div>

    <div class="section">
        <h2>Research Areas</h2>
        <h3>Federated Learning</h3>
        <p>FLAIR lab focuses on Federated Learning (FL), conducting in-depth research on several key areas:
        <p><b>Data Heterogeneity:</b> We study how to effectively train models when data distributions vary significantly across different participants. This includes developing robust optimization algorithms and adaptive model update methods.</p>
        <p><b>Communication Overhead:</b> To reduce the significant communication overhead in FL, we propose efficient compression techniques. We also explore methods to decrease communication frequency and data transmission while maintaining model performance.</p>
        <p><b>Large Language Models + FL:</b> We explore integrating large language models (LLMs) with FL to leverage their powerful capabilities in distributed data environments. This involves effectively training LLMs within FL, optimizing parameter synchronization, and developing FL algorithms suited for LLMs.</p>
    </div>

    <div class="section">
        <h2>Recent Publications</h2>

        <h3>Federated Learning and Edge Computing</h3>
        <ul>
            <li>Haolin Wang, Xuefeng Liu, Jianwei Niu*, Wenkai Guo, Shaojie Tang. Why Go Full? Elevating Federated Learning Through Partial Network Updates. Advances in Neural Information Processing Systems, NeurIPS 2024 (CCF A)</li>
            <li>Xinghao Wu, Xuefeng Liu, Jianwei Niu, Haolin Wang, Shaojie Tang, Guogang Zhu, Hao Su. Decoupling General and Personalized Knowledge in Federated Learning via Additive and Low-rank Decomposition. ACM MULTIMEDIA 2024, ACM MM 2024 (CCF A)</li>
            <li>Guogang Zhu, Xuefeng Liu, Jianwei Niu, Shaojie Tang, Xinghao Wu, Jiayuan Zhang. DualFed: Enjoying both Generalization and Personalization in Federated Learning via Hierachical Representations. ACM MULTIMEDIA 2024, ACM MM 2024, (CCF A)</li>
            <li>Guogang Zhu, Xuefeng Liu*, Jianwei Niu, Yucheng Wei, Shaojie Tang, Jiayuan Zhang. Learning by imitating the classics: Mitigating class imbalance in federated learning via simulated centralized learning. Expert Systems with Applications, ESWA 2024 (CCF C，中科院一区，TOP期刊)</li>
            <li>Jiayuan Zhang, Xuefeng Liu*, Yukang Zhang, Guogang Zhu, Jianwei Niu, Shaojie Tang. Enabling Collaborative Test-Time Adaptation in Dynamic Environment via Federated Learning[C]. Conference on Knowledge Discovery and Data Mining, KDD 2024 (CCF A)</li>
            <li>Guogang Zhu, Xuefeng Liu*, Xinghao Wu, Shaojie Tang, Chao Tang, Jianwei Niu, Hao Su. Estimating before Debiasing: A Bayesian Approach to Detaching Prior Bias in Federated Semi-Supervised Learning. The 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024 (CCF A)</li>
            <li>Yixuan Guan, Xuefeng Liu, Tao Ren, Jianwei Niu*. FedMDC: Enabling Communication-efficient Federated Learning over Packet Lossy Networks via Multiple Description Coding. 2024 IEEE International Conference on Multimedia and Expo, ICME 2024 (CCF B)</li>
            <li>Yixuan Guan, Xuefeng Liu*, Jianwei Niu, Tao Ren. FedTC: Enabling Communication-Efficient Federated Learning via Transform Coding, INFOCOM 2024 (CCF A)</li>
            <li>Xinghao Wu, Xuefeng Liu, Jianwei Niu, Guogang Zhu, and Shaojie Tang. Bold but Cautious: Unlocking the Potential of Personalized Federated Learning through Cautiously Aggressive Collaboration. ICCV, 2023. (CCF-A)</li>
            <li>Guogang Zhu, Xuefeng Liu*, Shaojie Tang, and Jianwei Niu. Aligning before Aggregating: Enabling Communication Efficient Cross-Domain Federated Learning via Consistent Feature Extraction. IEEE Transactions on Mobile Computing, 2023. (CCF-A)</li>
            <li>Yixuan Guan, Xuefeng Liu*, Tao Ren, Jianwei Niu. Enabling Communication-Efficient Federated Learning via Distributed Compressed Sensing, INFOCOM 2022. (CCF A)</li>
            <li>Pan Deng, Xuefeng Liu, Jianwei Niu, Chunming Hu. GraphFed: A Personalized Subgraph Federated Learning Framework for Non-IID Graphs[C]. IEEE 20th International Conference on Mobile Ad Hoc and Smart Systems (MASS), 2023. (CCF-C)</li>
            <li>Yixuan Guan, Xuefeng Liu*, Tao Ren, Jianwei Niu, Enabling Communication-Efficient Federated Learning via Distributed Compressed Sensing, INFOCOM 2022. (CCF A)</li>
            <li>Tao Ren, Zheyuan Hu, Hang he, Xuefeng Liu, Jianwei Niu, EAT: Towards Fast Environment-Adaptive Task Offloading and Power Allocation in MEC. INFOCOM 2022. (CCF A)</li>
            <li>Haolin Wang, Xuefeng Liu*, Jianwei Niu, Shaojie Tang, SVDFed: Enabling Communication-Efficient Federated Learning via Singular-Value-Decomposition. INFOCOM 2022. (CCF A )</li>
            <li>Guogang Zhu, Xuefeng Liu* Shaojie Tang, Jianwei Niu,, Aligning before Aggregating: Enabling Cross-domain Federated Learning via Consistent Feature Extraction. ICDCS 2022. (CCF B)</li>
            <li>Xinghao Wu, Jianwei Niu, Xuefeng Liu*, Tao Ren, Zhangmin Huang, Zhetao Li, pFedGF: Enabling Personalized Federated Learning via Gradient Fusion. IPDPS 2022. (CCF B)</li>
            <li>Kaiyu Zheng, Xuefeng Liu, Guogang Zhu, Xinghao Wu, Jianwei Niu. ChannelFed: Enabling Personalized Federated Learning via Localized Channel Attention. IEEE GLOBECOM 2022. (CCF C)</li>
            <li>Yanan Fu, Xuefeng Liu*, Shaojie Tang, Jianwei Niu & Zhangmin Huang. CIC-FL: enabling class imbalance-aware clustered federated learning over shifted distributions. Database Systems for Advanced Applications: 26th International Conference, 2021. (CCF B)</li>
            <li>Yibo Luo; Xuefeng Liu*; Jianwei Xiu. Energy-efficient clustering to address data heterogeneity in federated learning.2021-IEEE International Conference on Communications, 2021. (CCF C)</li>
            <li>Tao Ren, Jianwei Niu, Jiahe Cui, Zhenchao Ouyang, Xuefeng Liu. An application of multi-objective reinforcement learning for efficient model-free control of canals deployed with IoT networks[J]. Journal of Network and Computer Applications, 2021. (CCF C)</li>
            <li>Tao Ren, Jianwei Niu, Bin Dai, Xuefeng Liu, Zheyuan Hu, Mingliang Xu, Mohsen Guizani. Enabling efficient scheduling in large-scale UAV-assisted mobile-edge computing via hierarchical reinforcement learning. IEEE Internet of Things Journal, 2021. (中科院一区)</li>
            <li>Xuefeng Liu, Tianye Yang, Shaojie Tang, Peng Guo, and Jianwei Niu, “From Relative Azimuth to Absolute Location: Pushing the Limit of PIR Sensor based Localization", Mobicom 2020. (CCF A)</li>
            <li>Jiaping Lin; Jianwei Niu; Xuefeng Liu; Mohsen Guizani, "Protecting Your Shopping Preference With Differential Privacy," in IEEE Transactions on Mobile Computing, 2021. (CCF A)</li>
        </ul>

        <h3>AI and Healthcare</h3>
        <ul>
            <li>Xiaozheng Xie, Jianwei Niu, Xuefeng Liu*, Zhengsu Chen, Shaojie Tang, Shui Yu. A Survey on Incorporating Domain Knowledge into Deep Learning for Medical Image Analysis. Medical Image Analysis, (Q1, 高被引)</li>
            <li>Xiaozheng Xie, Chen Chen, Xuefeng Liu*, Yong Wang, Rui Wang, and Jianwei Niu. IMAN: An Iterative Mutual-Aid Network for Breast Lesion Segmentation on Multi-modal Ultrasound Images. IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2023). (CCF B)</li>
            <li>Xiaozheng Xie, Jianwei Niu, Xuefeng Liu*, Yong Wang, Qingfeng Li, Shaojie Tang. A Domain Knowledge Powered Hybrid Regularization Strategy for Semi-supervised Breast Cancer Diagnosis. Expert Systems with Applications, 2024. (JCR Q1)</li>
            <li>Han Wang, Jianwei Niu, Xuefeng Liu*, Yong Wang. A Doctors Behavior Aware and Domain Knowledge Driven Model for Medical Reports Generation. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2023. (CCF-B)</li>
            <li>Hui Meng, Xuefeng Liu, Jianwei Niu, Yong Wang, Jintang Liao, Qingfeng Li, Chen Chen. DGANet: A Dual Global Attention Neural Network for Breast Lesion Detection in Ultrasound Images. Ultrasound in Medicine & Biology, 2022.</li>
            <li>Han Wang, Jianwei Niu, Xuefeng Liu, Yong Wang. Embracing Uniqueness: Generating Radiology Reports via a Transformer with Graph-based Distinctive Attention. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2022. (CCF-B)</li>
            <li>Shaokang Yang, Jianwei Niu, Jiyan Wu, Yong Wang, Xuefeng Liu, Qingfeng Li. Automatic ultrasound image report generation with adaptive multimodal attention mechanism. Neurocomputing, 2021.</li>
            <li>Kaili Mao, Jianwei Niu, Xuefeng Liu*, Shaojie Tang, Lizi Liao, Tat-Seng Chua. A patience-aware recommendation scheme for shared accounts on mobile devices. IEEE Transactions on Knowledge and Data Engineering(TKDE),2021. (CCF A)</li>
            <li>Chen Chen, Yong Wang, Jianwei Niu, Xuefeng Liu*, Qingfeng Li, Xuantong Gong. Domain knowledge powered deep learning for breast cancer diagnosis based on contrast-enhanced ultrasound videos. IEEE Transactions on Medical Imaging, 2021. (CCF B)</li>
            <li>Hui Meng, Qingfeng Li, Xuefeng Liu, Yong Wang, JianWei Niu. "Multi-scale view-based convolutional neural network for breast cancer classification in ultrasound images." Medical Imaging 2021: Computer-Aided Diagnosis,2021.</li>
            <li>Xiaozheng Xie, Jianwei Niu, Xuefeng Liu*, A Survey on Incorporating Domain Knowledge into Deep Learning for Medical Image Analysis, Medical Imaging Analysis, 2020.</li>
            <li>Shaokang Yang, Jianwei Niu, Jiyan Wu, Xuefeng Liu. Automatic medical image report generation with multi-view and multi-modal attention mechanism. International Conference on Algorithms and Architectures for Parallel Processing, 2020. (CCF C)</li>
        </ul>

        <h3>Computer Vision</h3>
        <ul>
            <li>NaNa Wang, JianWei Niu, Xuefeng Liu, Dongqin Yu, Guogang Zhu, Xinghao Wu, Mingliang Xu, Hao Su. BeyondVision: An EMG-driven Micro Hand Gesture Recognition Based on Dynamic Segmentation. The 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024 (CCF A)</li>
            <li>Wei Chen, Jianwei Niu, Xuefeng Liu*. MRCAP: Multi-Modal and Multi-Level Relationship-Based Dense Video Captioning. IEEE International Conference on Multimedia and Expo (ICME), 2023. (CCF-B)</li>
            <li>Hao Su, Xuefeng Liu, Jianwei Niu, Jiahe Cui, Ji Wan, Xinghao Wu, Nana Wang. MARVEL: Raster Gray-level Manga Vectorization via Primitive-wise Deep Reinforcement Learning. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2023. (CCF-B)</li>
            <li>Hao Su, Jianwei Niu, Xuefeng Liu, Qingfeng Li, Ji Wan, Mingliang Xu, Tao Ren. ArtCoder: An End-to-end Method for Generating Scanning-robust Stylized QR Codes. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. (CCF A)</li>
            <li>Hao Su, Jianwei Niu, Xuefeng Liu, Qingfeng Li, Ji Wan, Mingliang Xu. Q-Art Code: Generating Scanning-robust Art-style QR Codes by Deformable Convolution. The 29th ACM International Conference on Multimedia (ACM MM), 2021. (CCF A)</li>
            <li>Zhengsu Chen, Lingxi Xie, Jianwei Niu, Xuefeng Liu, Longhui Wei, Qi Tian. Visformer: The Vision-friendly Transformer. ICCV, 2021. (CCF A)</li>
            <li>Wei Chen, Xuefeng Liu, Jianwei Niu.  SentiStory: A Multi-layered Sentiment-Aware Generative Model for Visual Storytelling. IEEE Transactions on Circuits and Systems for Video Technology, 2022.(CCF B)</li>
            <li>Hao Su, Jianwei Niu, Xuefeng Liu, Qingfeng LI, Jiahe Cui, Ji Wan. "Mangagan: Unpaired photo-to-manga translation based on the methodology of manga drawing." Proceedings of the AAAI Conference on Artificial Intelligence(AAAI), 2021. (CCF A)</li>
            <li>Lulu Zhang, HuiYong Li, Xuefeng Liu, Jianwei Niu, Jiyan Wu, "MobileSR: Efficient Convolutional Neural Network for Super-resolution," GLOBECOM 2020-2020 IEEE Global Communications Conference, 2020. (CCF C)</li>
            <li>Hao Su, Jianwei Niu, Xuefeng Liu, Qingfeng Li, Ji Wan, Mingliang Xu, Tao Ren. ArtCoder: An End-to-end Method for Generating Scanning-robust Stylized QR Codes[C]. IEEE Conference on Computer Vision and Pattern Recognition(CVPR), 2021. (CCF A)</li>
            <li>Hao Su, Jianwei Niu, Xuefeng Liu, Qingfeng Li, Ji Wan, Mingliang Xu. Q-Art Code: Generating Scanning-robust Art-style QR Codes by Deformable Convolution[C]. The 29th ACM International Conference on Multimedia(ACM MM), 2021.(CCF A)</li>
            <li>Zhengsu Chen, Lingxi Xie, Jianwei Niu, Xuefeng Liu, Longhui Wei, Qi Tian. Visformer: The Vision-friendly Transformer[C]. ICCV, 2021, (CCF A)</li>
            <li>Zhengsu Chen, Jianwei Niu, Xuefeng Liu*, Shaojie Tang. SelectScale: mining more patterns from images via selective and soft dropout. IJCAI-PRICAI, 2020. (CCF A)</li>
            <li>Shaokang Yang, Jianwei Niu, Jiyan Wu, Yong Wang, Xuefeng Liu, Qingfeng Li. Automatic ultrasound image report generation with adaptive multimodal attention mechanism[J]. Neurocomputing, 2021.</li>
            <li>Zhengsu Chen, Jianwei Niu, Lingxi Xie, Xuefeng Liu, Longhui Wei, Qi Tian. "Network adjustment: Channel search guided by flops utilization ratio." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition(CVPR), 2020. (CCF A)</li>
        </ul>
    </div>
</div>

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