Dr. Yi Zhou (周毅 Joey)
Ph.D., Associate Professor
IEEE, CCF, CSIG, JSAI Member, Google Scholar
School of Computer Science and Engineering, Southeast University
Office: Room 150, School of Computer Science and Engineering, Southeast University Jiulonghu Campus, Nanjing, Jiangsu, China.
I am a member of PAttern Learning and Mining (PALM) Lab.
Brief Biography
Dr. Yi Zhou is currently an associate professor with the school of computer science and engineering, Southeast University, China. Before joining SEU, he was a research scientist for three years, with the Inception Institute of Artificial Intelligence (IIAI), United Arab Emirates. He received the Ph.D. degree from the school of computing sciences, University of East Anglia, U.K., in 2018 and the M.Sc. degree from the department of electronic and electrical engineering, University of Sheffield, U.K., in 2014. His research interests include computer vision, machine learning, deep learning, and medical image analysis. He has authored/co-authored 35+ academic papers in top journals/conferences such as IEEE TPAMI, TIP, TMI, CVPR, ICCV, ECCV, AAAI, MICCAI, etc. He has also been granted with two US patents, as the first inventor.
周毅，博士，现任东南大学计算机科学与工程学院副教授，在PALM实验室工作。2013年至2018年，获全额奖学金，分别赴英国谢菲尔德大学与英国东安格利亚大学留学，师从邵岭教授，并获得硕士、博士学位。2018年至2021年加入阿联酋起源人工智能研究院（IIAI），担任研究科学家。研究工作领域主要包括：计算机视觉，模式识别，机器学习，深度学习，医学影像分析与识别，智能图像视频理解等。周毅已在领域内国际权威的期刊会议（例如IEEE TPAMI, TIP, TMI, CVPR, ICCV, ECCV, AAAI, MICCAI等）发表35+篇论文，被引2500余次，并获5项中/美发明专利, 主持/参与多项国家自然科学基金、江苏省自然科学基金等纵横向项目。学术兼职包括中国视觉与学习青年学者研讨会（VALSE） 执行领域主席，中国计算机学会计算机视觉、人工智能与模式识别专委会委员，江苏省人工智能学会模式识别、医学图像处理专委会委员，IEEE、CCF、CSIG、JSAI会员，并担任十多个国际顶级期刊会议审稿人。入选江苏省“双创博士”、南京市留学择优人才、东南大学“至善青年学者”A层次、东南大学“小米青年学者”等。
欢迎对我研究方向有浓厚兴趣 (Self-motivated!!!)，数学优秀，编程能力扎实的同学，与我一起工作！(欢迎2024级保研申请同学与我邮件联系！)
也特别欢迎优秀的本科生联系我，进行全面的学术科研、竞赛训练！
Research Interests
Vision and Language - Visual Detection and Segmentation, Generative Multimodal Reasoning
Machine Learning, Deep Learning - Open-World Transfer Learning, Multi-Task Learning, Lifelong/Continual Learning.
Medical Image Analysis - Disease Diagnosis, Medical Prognosis Prediction
Selected Publications
Huang, L., Qin, J., Zhou, Y., Zhu, F., Liu, L., and Shao, L., 2023. Normalization Techniques in Training DNNs: Methodology, Analysis and Application. IEEE Transactions on Pattern Analysis and Machine Intelligence. DOI: 10.1109/TPAMI.2023.3250241 [CCF-A类，中科院一区]
Liu, X., Zhou, Y.*, Zhou, T., and Qin, J., 2023. Self-Paced Learning for Open-Set Domain Adaptation. Journal of Computer Research and Development (计算机研究与发展). [CCF-A类]
Zhou, T., Zhou, Y., He, K., Gong, C., Yang, J., Fu, H., and Shen, D., 2023. Cross-level Feature Aggregation Network for Polyp Segmentation. Pattern Recognition. DOI: j.patcog.2023.109555 [CCF-B类，JCR-1区]
Yang, H., Zhou, T., Zhou, Y., Zhang, Y., Fu, H., 2023. Flexible Fusion Network for Multi-modal Brain Tumor Segmentation. IEEE Journal of Biomedical and Health Informatics. DOI: 10.1109/JBHI.2023.3271808 [JCR-1区]
Zhou, H., Huang, Y., Li, Y., Zhou, Y.*, Zheng, Y., 2023. Blind Super-Resolution of 3D MRI via Unsupervised Domain Transformation. IEEE Journal of Biomedical and Health Informatics. DOI: 10.1109/JBHI.2022.3232511 [JCR-1区]
Zhou, T., Zhou, Y., Gong C., Yang, J., Zhang, Y., 2022. Feature Aggregation and Propagation Network for Camouflaged Object Detection. IEEE Transactions on Image Processing. DOI: 10.1109/TIP.2022.3217695 [CCF-A类，中科院一区]
Zhou, T., Fan, D., Chen,G., Zhou, Y., and Fu, H., 2022. Specificity-Preserving RGB-D Saliency Detection. Computational Visual Media. DOI:10.1007/s41095 [JCR-1区]
Zhou, Y., Bai, S., Zhou, T., Zhang, Y., Fu, H., 2022. Delving into Local Features for Open-Set Domain Adaptation in Fundus Image Analysis. International Conference on Medical Imaging Computing and Computer Assisted Intervention (MICCAI), Singapore. [CCF-B类]
Huang, L., Zhou, Y., Wang, T., Luo, J., Liu, X., 2022. Delving into the Estimation Shift of Batch Normalization in a Network. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), New Orleans, USA. IEEE. [CCF-A类]
Zhou, Y., Huang, L., Zhou, T., Sun, H., 2022. Combating Medical Noisy Labels by Disentangled Distribution Learning and Consistency Regularization. Future Generation Computer Systems. DOI: 10.1016/j.future.2022.12.018 [JCR-1区]
Zhou, Y., Huang, L., Zhou, T., Fu, H., Shao, L., 2021. Visual-Textual Attentive Semantic Consistency for Medical Report Generation. IEEE International Conference on Computer Vision (ICCV), Virtual Online. IEEE. [CCF-A类]
Zhou, Y., Huang, L., Zhou, T., Shao, L., 2021. CCT-Net: Category-Invariant Cross-Domain Transfer for Medical Single-to-Multiple Disease Diagnosis. IEEE International Conference on Computer Vision (ICCV), Virtual Online. IEEE. [CCF-A类]
Zhou, T., Fu, H., Zhou, Y., Chen, G., Fan, D., Shao, L., 2021. Specificity-Preserving RGB-D Saliency Detection. IEEE International Conference on Computer Vision (ICCV), Virtual Online. IEEE. [CCF-A类]
Huang, L., Zhou, Y., Liu, L., Zhu, F., and Shao L., 2021. Group Whitening: Balancing Learning Efficiency and Representational Capacity. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Virtual Online. IEEE. [CCF-A类]
Zhou, Y., Zhou, T., Zhou, T., Fu, H., and Shao, L., 2021. Contrastive-Attentive Thoracic Disease Recognition with Dual-Weighting Graph Reasoning. IEEE Transactions on Medical Imaging. DOI: 10.1109/TMI.2021.3049498 [CCF-B类，中科院一区]
Zhou, Y., Wang, B., He, X., Cui, S., and Shao, L., 2021. DR-GAN: Conditional Generative Adversarial Network for Fine-Grained Lesion Synthesis on Diabetic Retinopathy Images. IEEE Journal of Biomedical and Health Informatics. DOI: 10.1109/JBHI.2020.3045475 [JCR-1区]
Zhou, Y., Huang, L., Zhou, T., and Shao L., 2021. Many-to-One Distribution Learning and K-Nearest Neighbour Smoothing for Thoracic Disease Identification. Thirty-Fifth AAAI Conference on Artificial Intelligence, Virtual Conference. [CCF-A类]
Li, X., Zhou, T., Li J., Zhou, Y., and Zhang, Z., 2021. Group-Wise Semantic Mining for Weakly Supervised Semantic Segmentation. Thirty-Fifth AAAI Conference on Artificial Intelligence, Virtual Conference. [CCF-A类]
Zhou, Y., Wang, B., Huang, L., Cui, S., and Shao, L., 2020. A Benchmark for Studying Diabetic Retinopathy: Segmentation, Grading, and Transferability. IEEE Transactions on Medical Imaging. DOI: 10.1109/TMI.2020.3037771 [CCF-B类，中科院一区]
Fan, D., Zhou, T., Ji, G., Zhou, Y., Chen, G., Fu, H., Shen, J., and Shao, L., 2020. Inf-Net: Automatic COVID-19 Lung Infection Segmentation from CT Images. IEEE Transactions on Medical Imaging. DOI: 10.1109/TMI.2020.2996645 [CCF-B类，中科院一区]
Huang, L., Zhao, L., Zhou, Y., Zhu, F., Liu, L. and Shao, L., 2020, June. An Investigation into the Stohastic of Batch Whitening. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, USA. IEEE. [CCF-A类]
Zhou, T., Wang, S., Zhou, Y., Yao, Y., Li, J. and Shao, L., 2020, Feb. Motion-Attentive Transition for Zero-Shot Video Object Segmentation. Thirty-Fourth AAAI Conference on Artificial Intelligence, New York, USA. [CCF-A类]
Zhou, Y., He, X., Cui., S, Zhu, F., Liu., L and Shao, L., 2019, Oct. High-Resolution Diabetic Retinopathy Image Synthesis Manipulated by Grading and Lesions. International Conference on Medical Imaging Computing and Computer Assisted Intervention (MICCAI), Shenzhen, China. [CCF-B类]
He, X., Zhou, Y., Wang, B., Cui, S. and Shao, L., 2019, Oct. DME-Net: Diabetic Macular Edema Grading by Auxiliary Task Learning. International Conference on Medical Imaging Computing and Computer Assisted Intervention (MICCAI), Shenzhen, China.[CCF-B类]
Zhou, Y., He, X., Huang, L., Liu, L., Zhu, F., Cui, S. and Shao, L., 2019, Jun. Collaborative Learning of Semi-Supervised Segmentation and Classification for Medical Images. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, USA. IEEE. [CCF-A类]
Huang, L., Zhou, Y., Zhu, F., Liu, L., and Shao, L., 2019, Jun. Iterative Normalization: Beyond Standardization towards Efficient Whitening. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, USA. IEEE. [CCF-A类]
Zhen, W., Zhang, J., Liu, L., Zhu, F., Shen, Zhou, Y., F., Sun, Y., Liu, S., Shao, L., 2019, Jun. Building Detail-Sensitive Semantic Segmentation Networks with Polynomial Pooling. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, USA. IEEE. [CCF-A类]
Zhou, Y. and Shao, L., 2018, Jun. Viewpoint-aware Attentive Multi-view Inference for Vehicle Re-identification. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, USA. IEEE. [CCF-A类]
Zhou, Y. and Shao, L., 2018, Mar. Vehicle Re-identification by Adversarial Bi-directional LSTM Network. IEEE Winter Conference on Applications of Computer Vision (WACV), Lake Tahoe, USA. IEEE. [CCF-C类]
Zhou, Y., Liu, L. and Shao, L., 2018. Vehicle Re-identification by Deep Hidden Multi-View Inference. IEEE Transactions on Image Processing. DOI: 10.1109/TIP.2018.2819820 [CCF-A类，中科院一区]
Liu, L., Zhou, Y. and Shao, L., 2018. Deep Action Parsing in Videos with Large-scale Synthesized Data. IEEE Transactions on Image Processing. DOI: 10.1109/TIP.2018.2813530 [CCF-A类，中科院一区]
Zhou, Y., Liu, L., Shao, L. and Mellor, M., 2017. Fast Automatic Vehicle Annotation for Urban Traffic Surveillance. IEEE Transactions on Intelligent Transportation Systems. DOI: 10.1109/TITS.2017.2740303 [CCF-B类，中科院一区]
Zhou, Y. and Shao, L., 2017, Sep. Cross-View GAN Based Vehicle Generation for Re-identification. Proceedings of the British Machine Vision Conference (BMVC), London, UK. BMVA Press. [CCF-C类]
Liu, L., Zhou, Y. and Shao, L., 2017, May. DAP3D-Net: Where, what and how actions occur in videos? In Robotics and Automation (ICRA), 2017 IEEE International Conference on (pp. 138-145), Singapore. IEEE. [CCF-B类]
Zhou, Y., Liu, L., Shao, L. and Mellor, M., 2016, October. DAVE: a unified framework for fast vehicle detection and annotation. In European Conference on Computer Vision (ECCV) (pp. 278-293), Amsterdam. Springer International Publishing. [CCF-B类]
Patents
周毅，刘星宏. 一种基于自步学习的开放集图像分类领域自适应方法，国家发明专利，受理时间：2023.4.20，申请号：CN202310427403.3.
黄雅雯，郑冶枫，周鹤翔，周毅. 图像生成模型的训练方法、图像生成方法、装置及设备，国家发明专利，受理时间：2022.4.22，申请号：CN202210431484.X.
黄雅雯，郑冶枫，袁一啸，周毅. 图像补全方法、装置、设备及存储介质，国家发明专利，受理时间：2022.4.27，申请号：CN202210457083.1.
Yi Zhou and Ling Shao, U.S. Patent No. 16/353,800, 2019
Title: Medical Images Segmentation and Severity Grading Using Neural Network Architectures with Semi-Supervised Learning Techniques.
Yi Zhou and Ling Shao, U.S. Patent No. 10/176,405, 2018
Title: Vehicle Re-identification techniques using neural networks for image analysis, viewpoint-aware pattern recognition, and generation of multi-view vehicle representations.
Projects and Contest Awards
国家自然科学基金青年项目，面向医学影像多病种诊断的开集域自适应迁移算法研究，主持，2022.01-2024.12
江苏省自然科学基金青年项目，面向眼底多病种识别中数据域任务域双偏移的算法研究，主持，2021.07-2024.06
南京市留学人员科技创新择优项目，基于开放环境下领域迁移的眼科智能诊断，主持，2023.01-2023.12
东南大学至善青年学者资助项目，面向低资源场景医学图像的标记高效学习算法研究，主持，2023.01-2025.12
江苏省自然科学基金面上项目，基于深度学习的多模态无监督视频聚类方法研究，参与，2021.07-2024.06
2021腾讯觅影医学人工智能算法大赛 - 眼底多病种诊断赛道 - 季军，2021.08-2021.11
Academic Services
Reviewer / PC Member for
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Image Processing
IEEE Transactions on Medical Imaging
IEEE Transactions on Neural Networks and Learning Systems
IEEE Transactions on Intelligent Transportation Systems
IEEE Journal of Biomedical and Health Informatics
International Journal of Computer Vision
Medical Image Analysis
Pattern Recognition
Machine Intelligence Research
AAAI Conference on Artificial Intelligence (AAAI) 2022
European Conference on Computer Vision (ECCV) 2020, 2022
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020-2023
IEEE Conference on Computer Vision (ICCV) 2019, 2021, 2023
International Conference on Medical Imaging Computing and Computer-Assisted Intervention (MICCAI) 2020-2023
Teaching and Student Training Awards
春季学期，机器视觉与应用（双语）
暑期国际学校，机器视觉与应用（全英文，与英国牛津大学、新加坡国家科技局等科研院所老师联合授课）
教育部-华为“智能基座”先锋教师
东南大学青年教师授课竞赛 - 三等奖
东南大学校级优秀本科毕业（设计）论文指导
Contact Information
Email: yizhou@seu.edu.cn, yi.zhou@ieee.org