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
Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications (Southeast University), Ministry of Education, China
I am a member of PAttern Learning and Mining(PALM) Lab.
Brief Bio
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 with the Inception Institute of Artificial Intelligence (IIAI) for three years, Abu Dhabi, United Arab Emirates. He received his 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 and machine learning. He has authored/co-authored 40+ academic papers in top journal/conference such as IEEE TPAMI, IEEE TIP, IEEE TMI, CVPR, ICCV, ECCV, ICLR, AAAI, MICCAI. He has also been granted with several CN/US patents. He has been ranked among the world top 2% scientists in 2023.
周毅，bet356手机版唯一官网登录副教授，博士生導師，計算機科學系副主任，目前在新一代人工智能技術與交叉應用教育部重點實驗室、PALM實驗室工作。入選斯坦福全球2%科學家、江蘇省“雙創博士”、南京市留學擇優人才、bet356手机版唯一官网“至善青年學者”A層次、bet356手机版唯一官网“小米青年學者”、CCF-滴滴“蓋亞青年學者”等。2013年至2018年，獲全額獎學金，分别赴英國謝菲爾德大學與英國東安格利亞大學留學，師從邵嶺教授，并獲得碩士、博士學位。2018年至2021年加入阿聯酋起源人工智能研究院（IIAI），擔任研究科學家。研究工作領域主要包括：計算機視覺、機器學習、醫學影像分析與識别、智能圖像視頻理解等。周毅已在領域内國際權威的期刊/會議（例如IEEE TPAMI, IEEE TIP, IEEE TMI, CVPR, ICCV, ECCV, ICLR, AAAI, MICCAI等）發表40餘篇論文，被引3500餘次，6項中/美發明專利，主持/參與多項國家自然科學基金、江蘇省自然科學基金等縱橫向項目。學術兼職包括中國視覺與學習青年學者研讨會（VALSE）執行領域主席，醫學圖像計算青年研讨會（MICS）執行委員，中國計算機學會計算機視覺、人工智能與模式識别專委會委員，中國圖象圖形學學會機器視覺專委會委員，江蘇省人工智能學會模式識别、醫學圖像處理專委會委員，IEEE, CCF, CSIG, JSAI會員，并長期擔任十多個國際頂級期刊/會議審稿人。
Research Interests
Vision and Language: Data- and Knowledge-Driven Visual Understanding, and Visual Generation (AIGC)
Machine Learning (Deep Learning): Open-World Transfer Learning, Multi-Task Learning, Continual Learning, Multi-Modal Foundation Model and Prompt Engineering
Medical Image Analysis: Medical Disease Diagnosis, Medical Prognosis
歡迎對相關研究方向有濃厚興趣（Self-motivated !!!）、數學優秀、編程能力紮實的同學與我一起工作，每年招收1-2名博士生、5名碩士生左右。
也特别歡迎優秀的本科生跟組進行全面的科研訓練。
Selected Publications
Zhou, T., Zhou, Y., Li, G., Chen, G., & Shen, J. (2024) Uncertainty-aware Hierarchical Aggregation Network for Medical Image Segmentation. IEEE Transactions on Circuits and Systems for Video Technology. DOI:10.1109/TCSVT.2024.3370685. [CCF-B類]
Lai, Y., Zhou, Y.*, Liu, X., & Zhou, T. (2024). Memory-Assisted Sub-Prototype Mining for Universal Domain Adaptation. In Proceedings of the International Conference on Learning Representations (ICLR). [清華-A類]
Huang, L., Qin, J., Zhou, Y., Zhu, F., Liu, L., & Shao, L. (2023). Normalization techniques in training dnns: Methodology, analysis and application. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(8), 10173–10196. [CCF-A類]
Liu, X., Zhou, Y.*, Zhou T., & Qin J. (2023). Self-Paced Learning for Open-Set Domain Adaptation[J]. Journal of Computer Research and Development (計算機研究與發展), 60(8): 1711-1726. doi: 10.7544/issn1000-1239.202330210. [CCF-A類, Outstanding Paper Award]
Li, Y., Zhou, T., He, K., Zhou, Y., & Shen, D. (2023). Multi-scale Transformer Network with Edge-aware Pre-training for Cross-Modality MR Image Synthesis. IEEE Transactions on Medical Imaging, 42(11), 3395-3407. [CCF-B類]
Zhou, T., Zhou, Y., He, K., Gong, C., Yang, J., Fu, H., & Shen, D. (2023). Cross-level Feature Aggregation Network for Polyp Segmentation. Pattern Recognition, 140, 109555. [CCF-B類]
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, 27(7), 3349-3359. [JCR-Q1]
Zhou, T., Fan, D., Chen G., Zhou, Y., & Fu, H. (2023). Specificity-preserving RGB-D saliency detection. Computer Visual Media Journal, 9(2), 297-317. [JCR-Q1]
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, 31, 7036-7047. [CCF-A類]
Zhou, H., Huang, Y., Li, Y., Zhou, Y.*, & Zheng, Y. (2022). Blind Super-Resolution of 3D MRI via Unsupervised Domain Transformation. IEEE Journal of Biomedical and Health Informatics, 27(3), 1409-1418. [JCR-Q1]
Zhou, Y., Bai, S., Zhou, T., Zhang, Y., & Fu, H. (2022). Delving into Local Features for Open-Set Domain Adaptation in Fundus Image Analysis. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) (pp. 682-692). Cham: Springer Nature Switzerland. [CCF-B類]
Huang, L., Zhou, Y., Wang, T., Luo, J., & Liu, X. (2022). Delving into the estimation shift of batch normalization in a network. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 763-772).
Zhou, Y., Huang, L., Zhou, T., & Sun, H. (2022). Combating medical noisy labels by disentangled distribution learning and consistency regularization. Future Generation Computer Systems, 141, 567-576. [JCR-Q1]
Zhou, Y., Wang, B., He, X., Cui, S., & Shao, L. (2022). DR-GAN: conditional generative adversarial network for fine-grained lesion synthesis on diabetic retinopathy images. IEEE Journal of Biomedical and Health Informatics, 26(1), 56-66. [JCR-Q1]
Zhou, Y., Huang, L., Zhou, T., & Shao, L. (2021). CCT-Net: category-invariant cross-domain transfer for medical single-to-multiple disease diagnosis. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) (pp. 8260-8270). [CCF-A類]
Zhou, Y., Huang, L., Zhou, T., Fu, H., & Shao, L. (2021). Visual-textual attentive semantic consistency for medical report generation. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) (pp. 3985-3994). [CCF-A類]
Zhou, T., Fu, H., Chen, G., Zhou, Y., Fan, D. P., & Shao, L. (2021). Specificity-preserving RGB-D saliency detection. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) (pp. 4681-4691). [CCF-A類]
Zhou, Y., Zhou, T., Zhou, T., Fu, H., Liu, J., & Shao, L. (2021). Contrast-attentive thoracic disease recognition with dual-weighting graph reasoning. IEEE Transactions on Medical Imaging, 40(4), 1196-1206. [CCF-B類]
Huang, L., Zhou, Y., Liu, L., Zhu, F., & Shao, L. (2021). Group whitening: Balancing learning efficiency and representational capacity. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 9512-9521). [CCF-A類]
Zhou, Y., Huang, L., Zhou, T., & Shao, L. (2021). Many-to-one distribution learning and k-nearest neighbor smoothing for thoracic disease identification. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, No. 1, pp. 768-776). [CCF-A類]
Li, X., Zhou, T., Li, J., Zhou, Y., & Zhang, Z. (2021). Group-wise semantic mining for weakly supervised semantic segmentation. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, No. 3, pp. 1984-1992). [CCF-A類]
Zhou, Y., Wang, B., Huang, L., Cui, S., & Shao, L. (2020). A benchmark for studying diabetic retinopathy: segmentation, grading, and transferability. IEEE Transactions on Medical Imaging, 40(3), 818-828. [CCF-B類]
Fan, D. P., Zhou, T., Ji, G. P., Zhou, Y., Chen, G., Fu, H., ... & Shao, L. (2020). Inf-net: Automatic covid-19 lung infection segmentation from ct images. IEEE Transactions on Medical Imaging, 39(8), 2626-2637. [CCF-B類]
Huang, L., Zhao, L., Zhou, Y., Zhu, F., Liu, L., & Shao, L. (2020). An investigation into the stochasticity of batch whitening. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 6439-6448). [CCF-A類]
Zhou, T., Wang, S., Zhou, Y., Yao, Y., Li, J., & Shao, L. (2020). Motion-attentive transition for zero-shot video object segmentation. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 34, No. 07, pp. 13066-13073). [CCF-A類]
Zhou, Y., He, X., Cui, S., Zhu, F., Liu, L., & Shao, L. (2019). High-resolution diabetic retinopathy image synthesis manipulated by grading and lesions. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) (pp. 505-513). Cham: Springer International Publishing. [CCF-B類]
He, X., Zhou, Y., Wang, B., Cui, S., & Shao, L. (2019). Dme-net: Diabetic macular edema grading by auxiliary task learning. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) (pp. 788-796). Cham: Springer International Publishing. [CCF-B類]
Zhou, Y., He, X., Huang, L., Liu, L., Zhu, F., Cui, S., & Shao, L. (2019). Collaborative learning of semi-supervised segmentation and classification for medical images. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 2079-2088). [CCF-A類]
Huang, L., Zhou, Y., Zhu, F., Liu, L., & Shao, L. (2019). Iterative normalization: Beyond standardization towards efficient whitening. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 4874-4883). [CCF-A類]
Wei, Z., Zhang, J., Liu, L., Zhu, F., Shen, F., Zhou, Y., ... & Shao, L. (2019). Building detail-sensitive semantic segmentation networks with polynomial pooling. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 7115-7123). [CCF-A類]
Zhou, Y., & Shao, L. (2018). Viewpoint-aware attentive multi-view inference for vehicle re-identification. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 6489-6498). [CCF-A類]
Zhou, Y., & Shao, L. (2018). Vehicle re-identification by adversarial bi-directional lstm network. In 2018 IEEE Winter Conference on Applications of Computer Vision (WACV) (pp. 653-662). IEEE. [CCF-C類]
Zhou, Y., & Shao, L. (2018). Vehicle re-identification by deep hidden multi-view inference. IEEE Transactions on Image Processing, 27(7), 3275-3287. [CCF-A類]
Liu, L., Zhou, Y., & Shao, L. (2018). Deep action parsing in videos with large-scale synthesized data. IEEE Transactions on Image Processing, 27(6), 2869-2882. [CCF-A類]
Zhou, Y., Liu, L., Shao, L., & Mellor, M. (2017). Fast automatic vehicle annotation for urban traffic surveillance. IEEE Transactions on Intelligent Transportation Systems, 19(6), 1973-1984. [CCF-B類]
Zhou, Y., & Shao, L. (2017). Cross-view GAN based vehicle generation for re-identification. In British Machine Vision Conference (BMVC) (Vol. 1, pp. 1-12). [CCF-C類]
Liu, L., Zhou, Y., & Shao, L. (2017). Dap3d-net: Where, what and how actions occur in videos?. In 2017 IEEE International Conference on Robotics and Automation (ICRA) (pp. 138-145). IEEE. [CCF-B類]
Zhou, Y., Liu, L., Shao, L., & Mellor, M. (2016). DAVE: A unified framework for fast vehicle detection and annotation. In Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part II 14 (pp. 278-293). Springer International Publishing. [CCF-B類]
Patents
周毅，劉星宏. 一種基于自步學習的開放集圖像分類領域自适應方法，國家發明專利，受理時間：2023.04.20，申請号：202310427403.3
肖力行，史瑞潇，周毅. 面向開放世界目标檢測的障礙識别與避障方法及小車系統，國家發明專利，受理時間：2023.09.11，申請号：202311161444.9
黃雅雯，鄭冶楓，袁一嘯，周毅. 圖像補全方法、裝置、設備及存儲介質，國家發明專利，受理時間：2022.04.27，申請号：202210457083.1
黃雅雯，鄭冶楓，周鶴翔，周毅. 圖像生成模型的訓練方法、圖像生成方法、裝置及設備，國家發明專利，受理時間：2022.04.22，申請号：202210431484.X
Zhou, Yi, et al. Medical image segmentation and severity grading using neural network architectures with semi-supervised learning techniques. U.S. Patent No. 10,430,946. 1 Oct. 2019.
Zhou, Yi, and Ling Shao. Vehicle re-identification techniques using neural networks for image analysis, viewpoint-aware pattern recognition, and generation of multi-view vehicle representations. U.S. Patent No. 10,176,405. 8 Jan. 2019.
Projects and Contest Awards
國家自然科學基金青年項目，面向醫學影像多病種診斷的開集域自适應遷移算法研究，2022.01 – 2024.12，主持
江蘇省自然科學基金青年項目，面向眼底多病種識别中數據域任務域雙偏移的算法研究，2021.07 – 2024.06，主持
南京市留學人員科技創新擇優項目，基于開放環境下領域遷移的眼科智能診斷，2023.01 – 2023.12，主持
bet356手机版唯一官网至善青年學者資助項目，面向低資源場景醫學圖像的标記高效學習算法研究，2023.01 – 2025.12，主持
CCF – 滴滴蓋亞學者科研基金項目，面向道路場景的多模态多任務基礎模型研究，2023.09 – 2024.08，主持
江蘇省自然科學基金面上項目，基于深度學習的多模态無監督視頻聚類方法研究，2021.07 – 2024.06，參與
騰訊覓影醫學人工智能算法大賽，2021.08 – 2021.11，季軍
Academic Services
Reviewer / Program Committee
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
IEEE Transactions on Image Processing
IEEE Transactions on Neural Networks and Learning Systems
Pattern Recognition
IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Medical Imaging
Medical Image Analysis
IEEE Journal of Biomedical and Health Informatics
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020 - 2024
IEEE Conference on Computer Vision (ICCV) 2019 - 2023
European Conference on Computer Vision (ECCV) 2020 – 2024
Conference on Neural Information Processing Systems (NeurIPS) 2023
Association for the Advancement of Artificial Intelligence (AAAI) 2021 – 2024
International Conference on Medical Imaging Computing and Computer Assisted Intervention (MICCAI) 2020 - 2024
Teaching and Student Training Awards
機器視覺與應用（雙語），春季學期
機器視覺與應用（全英文），暑期國際學校（與英國、新加坡高校教師聯合授課）
教育部-XX“智能基座”先鋒教師
bet356手机版唯一官网第30屆青年教師授課競賽，三等獎
bet356手机版唯一官网校級學優生優秀指導教師
bet356手机版唯一官网校級本科優秀畢業設計（論文）指導教師
中國大學生計算機設計大賽江蘇省級賽特等獎，優秀指導教師
Contact Info.
Email: yizhou@seu.edu.cn; yi.zhou@ieee.org