【详细信息】
卢杨，博士，现为厦门大学bwin必赢计算机科学与技术系助理教授，博士生导师，人工智能研究院双聘导师，福建省优秀青年基金获得者，小米青年学者。2012年和2014年分别获得澳门大学软件工程专业本科和硕士学位。2019年获得香港浸会大学计算机科学专业博士学位。已发表高水平论文40余篇，其中多篇论文发表在机器学习一流期刊（JCR 1区）如IEEE TNNLS和IEEE TCYB等，以及人工智能和计算机视觉顶级会议（CCF-A类）如CVPR、ICCV、AAAI、IJCAI、ACMMM等。主持国家自然科学基金面上项目及青年项目、福建省新型智库重大课题、福建省自然科学基金面上项目、之江实验室开放课题等多个项目。任中国图象图形学学会机器视觉专委会委员、中国图象图形学学会厦门会员活动中心秘书长、以及国际知名期刊IEEE Transactions on Emerging Topics in Computational Intelligence责任编委（Associate Editor）。在智能优化领域重要会议DOCS 2024获得最佳论文奖。目前主要研究方向为面向开放世界的鲁棒深度学习，包含长尾学习、联邦学习、噪声标签学习、持续学习等机器学习前沿领域。
招收硕士生和对科研感兴趣的本科生，欢迎对深度学习、计算机视觉以及相关领域有兴趣的同学联系我。联系前请仔细阅读个人主页中的硕士招生简章（https://jasonyanglu.github.io/postgraduate/），未在邮件中注明“已了解招生简章并愿意接受考核”的均不予回复。更多信息请查看个人主页：https://jasonyanglu.github.io/。
【主讲课程】
1.离散数学（计算机科学与技术专业本科生必修课），2020秋季至今
2.深度学习（计算机科学与技术专业研究生选修课），2020秋季至今
3.算法设计与分析A（计算机科学与技术专业本科生必修课），2021春季
【科研项目】
1. 国家自然科学基金重点项目课题，面向复杂工业场景的多模态跨域异常检测方法研究，2025/01-2029/12，75万元，已获批，主持
2. 国家自然科学基金面上项目，面向标签非完备数据的联合监督深度学习方法研究，2024/01-2027/12，49万元，在研，主持
3. 国家自然科学基金青年项目，面向不平衡数据的联邦学习方法研究，2021/01-2023/12，24万元，已结题，主持
4. 福建省优秀青年科学基金，面向复杂数据场景的深度学习方法研究，2024/05-2027/04，20万元，在研，主持
5. 福建省新型智库重大课题，新人工智能革命下我省加快数字经济高质量发展研究，2024/01-2024/12，5万元，在研，主持
6. 福建省自然科学基金面上项目，基于深度集成网络的复杂场景在线学习方法研究，2020/11-2023/11，7万元，已结题，主持
7. 之江实验室开放课题，面向复杂异构数据的联邦学习方法研究，2021/01-2022/12，50万元，已结题，主持
8. 横向课题，基于目标检测的船舶自动导航系统，2021/07-2022/07，10万元，已结题，主持
9. 横向课题，基于联邦学习的智慧政务系统，2023/01-2023/12，20万元，在研，主持
10. 横向课题，基于视觉分析的工业缺陷检测系统，2023/08-2025/07，10万元，在研，主持
【代表性论文】
[IJCV’24] IMC-Det: Intra-Inter Modality Contrastive Learning for Video Object Detection
Qiang Qi, Zhenyu Qiu, Yan Yan, Yang Lu and Hanzi Wang
International Journal of Computer Vision, 2024. (JCR 1区 / CCF-A)
[SCIS’24] Wavelet-domain feature decoupling for weakly supervised multi-object tracking
Yu-Lei Li, Yan Yan, Yang Lu* and Hanzi Wang
Science China Information Sciences, vol. 67, no. 8, 189102, 2024. (JCR 2区 / CCF-A)
[TAI’24] Adjusting Logit in Gaussian Form for Long-Tailed Visual Recognition
Mengke Li, Yiu-ming Cheung, Yang Lu, Zhikai Hu, Weichao Lan, and Hui Huang.
IEEE Transactions on Artificial Intelligence, 2024.
[DOCS’24] Federated Clustering with Unknown Number of Clusters
Yiqun Zhang, Rong Zou, Yunfan Zhang, Yang Lu, Mengke Li and Yiu-ming Cheung
The 6th International Conference on Data-driven Optimization of Complex Systems, Hangzhou, China, August 26-18, 2024. (Best paper award)
[MM’24] Semi-supervised Visible-Infrared Person Re-identification via Modality Unification and Confidence Guidance
Xiying Zheng, Yukang Zhang, Yang Lu, and Hanzi Wang
ACM Multimedia, Melbourne, Australia, October 28 - November 1, accepted, 2024. (CCF-A)
[MM’24] Diverse consensuses paired with motion estimation-based multi-model fitting
Wenyu Yin, Shuyuan Lin, Yang Lu*, and Hanzi Wang
ACM Multimedia, Melbourne, Australia, October 28 - November 1, accepted, 2024. (CCF-A)
[MM’24] Robust Pseudo-label Learning with Neighbor Relation for Unsupervised Visible-Infrared Person Re-Identification
Xiangbo Yin, Jiangming Shi, Yachao Zhang, Yang Lu, Zhizhong Zhang, Yuan Xie, and Yanyun Qu
ACM Multimedia, Melbourne, Australia, October 28 - November 1, accepted, 2024. (CCF-A)
[SCIS’24] Wavelet-domain feature decoupling for weakly supervised multi-object tracking
Yu-Lei Li, Yan Yan, Yang Lu* and Hanzi Wang
Science China Information Sciences, vol. 67, no. 8, 189102:1-189102:2, 2024. (JCR 2区 / CCF-A)
[ECAI’24] Learning Order Forest for Qualitative-Attribute Data Clustering
Mingjie Zhao, Sen Feng, Yiqun Zhang, Mengke Li, Yang Lu, Yiu-Ming Cheung
European Conference on Artificial Intelligence, Santiago de Compostela, October 19-24, 2024. (CCF-B)
[IJCAI’24] Dynamically Anchored Prompting for Task-Imbalanced Continual Learning
Chenxing Hong, Yan Jin, Zhiqi Kang, Yizhou Chen, Mengke Li, Yang Lu* and Hanzi Wang
International Joint Conference on Artificial Intelligence, Jeju, Korea, August 3-9, 2024. (CCF-A)
[AAAI’24] Federated Learning with Extremely Noisy Clients via Negative Distillation
Yang Lu, Lin Chen, Yonggang Zhang, Yiliang Zhang, Bo Han, Yiu-ming Cheung, and Hanzi Wang
AAAI Conference on Artificial Intelligence, Vancouver, Canada, February 20–27, 2024. (CCF-A)
[AAAI’24] Feature Fusion from Head to Tail for Long-Tailed Visual Recognition
Mengke Li, Zhikai Hu, Yang Lu, Weichao Lan, Yiu-ming Cheung, and Hui Huang
AAAI Conference on Artificial Intelligence, Vancouver, Canada, February 20–27, 2024. (CCF-A)
[AAAI’24] CLIP-guided Federated Learning on Heterogeneous and Long-Tailed Data
Jiangming Shi, Shanshan Zheng, Xiangbo Yin, Yang Lu, Yuan Xie, and Yanyun Qu
AAAI Conference on Artificial Intelligence, Vancouver, Canada, February 20–27, 2024. (CCF-A)
[ICCV’23] Label-Noise Learning with Intrinsically Long-Tailed Data
Yang Lu, Yiliang Zhang, Bo Han, Yiu-ming Cheung, and Hanzi Wang
IEEE/CVF International Conference on Computer Vision, Paris, France, October 2-6, 2023. (CCF-A)
[TIP’23] DGRNet: A Dual-level Graph Relation Network for Video Object Detection
Qiang Qi, Tianxiang Hou, Yang Lu, Yan Yan, and Hanzi Wang
IEEE Transactions on Image Processing, vol. 32, pp. 4128-4141, 2023. (JCR 1区 / CCF-A)
[CVPR’23] Long-Tailed Visual Recognition via Self-Heterogeneous Integration with Knowledge Excavation
Yan Jin, Mengke Li, Yang Lu*, Yiu-ming Cheung, and Hanzi Wang
IEEE/CVF Conference on Computer Vision and Pattern Recognition, Vancouver, Canada, June 18-22, 2023. (CCF-A)
[IJCAI’22] Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features
Xinyi Shang, Yang Lu*, Gang Huang, and Hanzi Wang
International Joint Conference on Artificial Intelligence, pp.2218-2224, Vienna, Austria, July 23-29, 2022. (CCF-A)
[ICME’22] FEDIC: Federated Learning on Non-IID and Long-Tailed Data via Calibrated Distillation
Xinyi Shang, Yang Lu*, Yiu-ming Cheung, and Hanzi Wang
IEEE International Conference on Multimedia and Expo, pp.1-6, Taipei, Taiwan, July 18-22, 2022. (CCF-B)
[ICME’22] Dual Selection Network for Video Object Detection
Tianxiang Hou, Qiang Qi, Yang Lu, Kaiwen Du, and Hanzi Wang
IEEE International Conference on Multimedia and Expo, pp.1-6, Taipei, Taiwan, July 18-22, 2022. (CCF-B)
[TIE’22] Motion Consistency Guided Robust Geometric Model Fitting with Severe Outliers
Hanlin Guo, Yang Lu, Haosheng Chen, Hailing Luo, Guobao Xiao, Haifang Zhang, and Hanzi Wang
IEEE Transactions on Industrial Electronics, vol. 69, no. 4, pp. 4065-4075, 2022. (JCR 1区)
[CVPR’22] Long-tailed Visual Recognition via Gaussian Clouded Logit Adjustment
Mengke Li, Yiu-ming Cheung, and Yang Lu
IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.6929-6938, New Orleans, Louisiana, June 21–24, 2022. (CCF-A)
[ACMMM’21] Towards a Unified Middle Modality Learning for Visible-Infrared Person Re-Identification
Yukang Zhang, Yan Yan, Yang Lu, and Hanzi Wang
ACM International Conference on Multimedia, pp. 788–796, Chengdu, China, October 20-24, 2021. (CCF-A)
[ECML-PKDD’21] Small-Vote Sample Selection for Label-Noise Learning
Youze Xu, Yan Yan, Jing-hao Xue, Yang Lu, and Hanzi Wang
The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, pp. 729-744, Bilbao, Spain, September 13–17, 2021. (CCF-B)
[TCYB’21] Self-Adaptive Multi-Prototype-based Competitive Learning Approach: A k-means-type Algorithm for Imbalanced Data Clustering
Yang Lu, Yiu-ming Cheung, and Yuan Yan Tang
IEEE Transactions on Cybernetics, vol. 51, no. 3, pp. 1598-1612, 2021. (JCR 1区 / CCF-B)
[TNNLS’20] Bayes Imbalance Impact Index: A Measure of Class Imbalanced Dataset for Classification Problem
Yang Lu, Yiu-ming Cheung, and Yuan Yan Tang
IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 9, pp. 3525-3539, 2020. (JCR 1区 / CCF-B)
[TNNLS’20] Adaptive Chunk-based Dynamic Weighted Majority for Imbalanced Data Streams with Concept Drift
Yang Lu, Yiu-ming Cheung, and Yuan Yan Tang
IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 8, pp. 2764-2778, 2020. (JCR 1区 / CCF-B)
[IJCAI’17] Dynamic Weighted Majority for Incremental Learning of Imbalanced Data Streams with Concept Drift
Yang Lu, Yiu-ming Cheung, and Yuan Yan Tang
International Joint Conference on Artificial Intelligence, pp. 2393-2399, Melbourne, Australia, August 19-25, 2017. (CCF-A)
[TNNLS’17] k-Times Markov Sampling for SVMC
Bin Zou, Chen Xu, Yang Lu, Yuan Yan Tang, Jie Xu, and Xinge You
IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 4, pp. 1328-1341, 2017. (JCR 1区 / CCF-B)
[PAKDD’16] Hybrid Sampling with Bagging for Class Imbalance Learning
Yang Lu, Yiu-ming Cheung, and Yuan Yan Tang
Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 14-26, Auckland, New Zealand, April 19-22, 2016. (CCF-C)
[TGRS’15] Hyperspectral Image Classification Based on Three-Dimensional Scattering Wavelet Transform
Yuan Yan Tang, Yang Lu, and Haoliang Yuan
IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 5, pp. 2467-2480, 2015. (JCR 2区 / CCF-B)
[TCBB’15] A Fractal Dimension and Wavelet Transform Based Method for Protein Sequence Similarity Analysis
Lina Yang, Yuan Yan Tang, Yang Lu and Huiwu Luo
IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 12, no. 2, pp. 348-369, 2015. (JCR 3区 / CCF-B)
[TCYB’15] The Generalization Ability of SVM Classification Based on Markov Sampling
Jie Xu, Yuan Yan Tang, Bin Zou, Zong Ben Xu, Luo Qing Li, Yang Lu, and Baochang Zhang
IEEE Transactions on Cybernetics, vol. 45, no. 6, pp. 1169-1179, 2015. (JCR 1区 / CCF-B)
[TNNLS’14] The Generalization Ability of Online SVM Classification Based on Markov Sampling
Jie Xu, Yuan Yan Tang, Bin Zou, Zong Ben Xu, Luo Qing Li, Yang Lu, and Baochang Zhang
IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 3, pp. 628-639, 2014. (JCR 1区 / CCF-B)
[NN’14] Generalization performance of Gaussian kernels SVMC based on Markov sampling
Jie Xu, Yuan Yan Tang, Bin Zou, Zong Ben Xu, Luo Qing Li, and Yang Lu
Neural Networks, vol. 53, pp. 40-51, 2014. (JCR 2区 / CCF-B)
[TCYB’14] The Generalization Performance of Regularized Regression Algorithms Based on Markov Sampling
Bin Zou, Yuan Yan Tang, Zong Ben Xu, Luo Qing Li, Jie Xu, and Yang Lu
IEEE Transactions on Cybernetics, vol. 44, no. 9, pp. 1497-1507, 2014. (JCR 1区 / CCF-B)