个人简述：
卢永毅，广东工业大学“青年百人A”副教授。2018年博士毕业于香港科技大学计算机科学及工程学系，2019-2022年任美国约翰霍普金斯大学博士后研究员，导师为计算机视觉的权威Alan Yuille教授。在人工智能顶级会议期刊（ICCV/CVPR/ECCV/MICCAI/ICML /TPAMI等）发表学术论文30余篇，谷歌学术总引用量4500余次，单篇最高引用量3000余次。曾获ImageNet国际挑战赛（视频目标检测）总排名第6，申请美国专利2项。研究方向包括通用人工智能、计算机视觉、机器学习及其在智慧医疗、生成式AI的应用。
学科领域：
科学学位：信息与通信工程
专业学位：电子与通信工程
教育背景：
2014/09 – 2018/11，香港科技大学，计算机科学及工程学系，博士
2011/09 – 2014/07，中山大学，计算机软件与理论，硕士
2007/09 – 2011/07，中山大学，软件学院，本科
工作经历：
2019/01 – 2022/04，约翰霍普金斯大学（美国，马里兰州），博士后研究员
2017/01 – 2018/06，腾讯优图实验室（深圳），机器学习方向实习生
学术兼职：
担任CVPR/ICCV/ECCV/NeurIPS/ICLR/MICCAI/IJCV/Nature Machine Intelligence等期刊会议审稿人。
主要论文：
[1] Yongyi Lu, Yu-Wing Tai, Chi-Keung Tang. Attribute-Guided Face Generation Using Conditional CycleGAN. European Conference on Computer Vision (ECCV), 2018.
[2] Yongyi Lu, Shangzhe Wu, Yu-Wing Tai, Chi-Keung Tang. Image Generation from Sketch Constraint Using Contextual GAN. European Conference on Computer Vision (ECCV), 2018.
[3] Yongyi Lu, Cewu Lu, Chi-Keung Tang. Online Video Object Detection using Association LSTM. IEEE International Conference on Computer Vision (ICCV), 2017.
[4] Jieneng Chen, Yongyi Lu*, Qihang Yu, Xiangde Luo, Ehsan Adeli, Yan Wang, Le Lu, Alan L. Yuille, Yuyin Zhou. TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation. International Conference on Machine Learning (ICML) Workshop on Interpretable Machine Learning in Healthcare, 2021. （单篇引用3000+次，GitHub Star 2000+次）
[5] Yongkang He, Mingjin Chen, Yongyi Lu*, Zhijing Yang. Data-Centric Diet: Effective Multi-center Dataset Pruning for Medical Image Segmentation. International Conference on Machine Learning (ICML) Workshop on Interpretable Machine Learning in Healthcare, 2023.
[6] Yuan Yao, Fengze Liu, Zongwei Zhou, Yan Wang, Wei Shen, Alan Yuille, Yongyi Lu*. Unsupervised Domain Adaptation through Shape Modeling for Medical Image Segmentation. Medical Imaging with Deep Learning (MIDL), 2022.
[7] Zhuotun Zhu, Yongyi Lu*, Wei Shen, Elliot Fishman, Alan Yuille. Segmentation for Classification of Screening Pancreatic Neuroendocrine Tumors. International Conference on Computer Vision (ICCV) Workshop on Computer Vision for Automated Medical Diagnosis, 2021.
[8] Shuhao Fu, Yongyi Lu*, Yan Wang, Yuyin Zhou, Wei Shen, Elliot Fishman, Alan Yuille. Domain Adaptive Relational Reasoning for 3D Multi-Organ Segmentation. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020.
[9] Hanwen Cao, Yongyi Lu*, Bo Pang, Cewu Lu, Alan Yuille. ASAP-Net: Attention and Structure Aware Point Cloud Sequence Segmentation. The British Machine Vision Conference (BMVC), 2020.
其他会议论文：
[10] Shiyi Du, Xiaosong Wang, Yongyi Lu, Yuyin Zhou, Shaoting Zhang, Alan Yuille, Kang Li, Zongwei Zhou. Boosting Dermatoscopic Lesion Segmentation via Diffusion Models with Visual and Textual Prompts. ISBI, 2024.
[11] Jie Liu, Yixiao Zhang, Jie-Neng Chen, Junfei Xiao, Yongyi Lu, Yixuan Yuan, Alan Yuille, Yucheng Tang, Zongwei Zhou. CLIPDriven Universal Model for Organ Segmentation and Tumor Detection. IEEE International Conference on Computer Vision (ICCV), 2023.
[12] Liangyu Chen, Yutong Bai, Siyu Huang, Yongyi Lu, Bihan Wen, Alan Yuille, Zongwei Zhou. Making Your First Choice: To Address Cold Start Problem in Vision Active Learning. Medical Imaging with Deep Learning (MIDL), 2023.
[13] Tiange Xiang, Yixiao Zhang, Yongyi Lu, Alan Yuille, Chaoyi Zhang, Weidong Cai, Zongwei Zhou. SQUID: Deep Feature In- Painting for Unsupervised Anomaly Detection. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
[14] Mintong Kang, Bowen Li, Zengle Zhu, Yongyi Lu, Elliot K. Fishman, Alan Yuille, Zongwei Zhou. Label-Assemble: Leveraging Multiple Datasets with Partial Label. ISBI, 2023.
[15] Yupei Lin, Sen Zhang, Tianshui Chen, Yongyi Lu, Guangping Li, Yukai Shi. Exploring negatives in contrastive learning for unpaired image-to-image translation. ACM International Conference on Multimedia (MM), 2023.
[16] Qihang Yu, Yingda Xia, Yutong Bai, Yongyi Lu, Alan Yuille, Wei Shen. Glance-and-gaze vision transformer. Advances in Neural Information Processing Systems (NeurIPS), 2021.
[17] Cewu Lu, Hao Su, Yongyi Lu, Eric Yi, Chi-Keung Tang, Leonidas Guibas. Beyond Holistic Object Recognition: Enriching Image Understanding with Part States. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
[18] Cewu Lu, Yongyi Lu, Chi-Keung Tang. Square Localization for Efficient and Accurate Object Detection. IEEE International Conference on Computer Vision (ICCV), 2015.
[19] Yao Xiao, Cewu Lu, Yongyi Lu, Chi-Keung Tang. Complexity-Adaptive Distance Metric for Object Proposals Generation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
其他期刊论文：
[20] Tiange Xiang, Yixiao Zhang, Yongyi Lu, Alan Yuille, Zongwei Zhou. Exploiting Structural Consistency of Chest Anatomy for Unsupervised Anomaly Detection in Radiography Images. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
[21] Junpeng Tan, Xiaojun Yang, Zhijing Yang, Ruihan Chen, Yongyi Lu, Liang Lin. Extensible Max-min Collaborative Retention for Online Mini-batch Learning Hash Retrieval. IEEE Transactions on Multimedia (T-MM), 2024.
[22] Liang Lin, Yongyi Lu, Chenglong Li, Hui Cheng, and Wangmeng Zuo. Detection-free Multi-object Tracking by Reconfigurable Inference with Bundle Representations. IEEE Transactions on Cybernetics (T-Cybernetics), 2016.
[23] Liang Lin, Yongyi Lu, Yan Pan, and Xiaowu Chen. Integrating Graph Partitioning and Matching for Trajectory Analysis in Video Surveillance. IEEE Transactions on Image Processing (TIP), 2012.
教学活动：
本科生课程：《模式识别》、《大数据实时处理技术》、《专业导论》
我的团队：
科研团队：人工智能研发团队
学生培养：
计划2024年招收多名硕士生和经验丰富的本科生，希望同学：
（1）对科研有热情、思维活跃、积极主动；
（2）有较强编程能力，较强数学分析、算法能力；
（3）有深度学习科研项目背景优先考虑；
（4）有意愿继续攻读博士或出国深造者优先考虑，可协助推荐海外学校。
