职称

讲师

电子邮件

richzhou@shu.edu.cn

办公室

计411室

研究方向

模式识别、生物特征识别、稀疏学习、非完整多模态聚类

个人简介

周健航，博士，硕士生导师，上海大学讲师。2023年毕业于澳门大学获计算机科学哲学博士学位，2023-2025年于日本大阪大学从事博士后研究员工作。2025年入选上海市海外高层次人才计划。研究方向主要包括：模式识别、生物特征识别、稀疏学习、非完整多模态聚类等。共发表学术论文40余篇，授权专利1项，作为参与组织国际学术会议2次。与多个国家和地区的高校科研机构保持良好合作关系，包括：中国香港、中国澳门、日本、澳大利亚、加拿大等。近年来主持国家自然科学基金青年项目、上海市海外高层次人才专项等科研项目。作为骨干成员参与国家级科研项目1项。

教育背景

2020-2023, 澳门大学, 计算机科学专业, 博士

2018-2020, 澳门大学, 计算机科学专业, 硕士

2014-2018, 南京林业大学,计算机科学与技术专业, 学士

主要工作经历

2023-2025,日本大阪大学，博士后研究员

2010-2013, XX公司，xxx岗位

科研项目

2026-2028，面向医学生物特征识别的绿色学习方法，国家自然科学基金青年项目，负责人

2026-2028，上海市海外高层次人才专项，负责人

代表性论文或专著

• Alsherfawi, A., Zhou, J.*, Shehata, A., & Yagi, Y. (2025). Behavioral Signature Decoding: Facial Landmark-based Graph Learning for Cybernetic Avatar Authentication. 2025 IEEE International Joint Conference on Biometrics (IJCB2025).

• Ang, J., Zhou, J.*, & Wu, X. (2025). Privacy-preserving Facial-based Diagnosis with Shared-Attention Multitask Learning. 2025 IEEE International Joint Conference on Biometrics (IJCB2025).

• Zhou, J., Li, S., Zeng, S., & Zhang, B. (2024). Probabilistic Nuclear-Norm Matrix Regression Regularized by Random Graph Theory. IEEE Transactions on Emerging Topics in Computational Intelligence.

• Zhou, J., Zhang, Q., Zeng, S., Zhang, B., & Fang, L. (2024). Latent Linear Discriminant Analysis for feature extraction via Isometric Structural Learning. Pattern Recognition, 149, 110218.

• Zhou, J., Wang, G., Zeng, S., & Zhang, B. (2023). Learning with Euler Collaborative Representation for Robust Pattern Analysis. ACM Transactions on Intelligent Systems and Technology. 109, 1-25.

• Zhou, J., Zhang, B., & Zeng, S. (2022). Consensus Sparsity: Multi-context Sparse Image Representation via L∞-induced Matrix Variate. IEEE Transactions on Image Processing. 32, 603-616.

• Zhou, J., Zhang, Q., Zeng, S., & Zhang, B. (2022). Fuzzy Graph Subspace Convolutional Network. IEEE Transactions on Neural Networks and Learning Systems.

• Zhou, J., Zhang, B., Zeng, S., & Lai, Q. (2021). Joint Discriminative Latent Subspace Learning for Image Classification. IEEE Transactions on Circuits and Systems for Video Technology.

• Zhou, J., Zeng, S., & Zhang, B. (2021). Sparsity-Induced Graph Convolutional Network for Semisupervised Learning. IEEE Transactions on Artificial Intelligence, 2(6), 549-563.

• Zhou, J., Zeng, S., & Zhang, B. (2020). Two-stage knowledge transfer framework for image classification. Pattern Recognition, 107, 107529.

• Zhou, J., Zeng, S., & Zhang, B. (2022). Learning salient self-representation for image recognition via orthogonal transformation. Expert Systems with Applications 212, 212, 118663.

• Zhou, J., Zhang, Q., & Zhang, B. (2021). An automatic multi-view disease detection system via collective deep region-based feature representation. Future Generation Computer Systems, 115, 59-75.

• Zhou, J., Zeng, S., & Zhang, B. (2022). Kernel nonnegative representation-based classifier. Applied Intelligence, 52(2), 2269-2289.

• Zhou, J., Zhang, Q., & Zhang, B. (2021). Two-phase non-invasive multi-disease detection via sublingual region. Computers in Biology and Medicine, 137, 104782.

• Zhang, B., & Zhou, J. (2021). Multi-feature representation for burn depth classification via burn images. Artificial Intelligence in Medicine, 118, 102128.

• Zhou, J., Zhang, Q., & Zhang, B. (2020, September). A progressive stack face-based network for detecting diabetes mellitus and breast cancer. In 2020 IEEE International Joint Conference on Biometrics (IJCB) (pp. 1-9). IEEE. [paper]

• Zhou, J., Zeng, S., & Zhang, B. (2021). Subspace-level dictionary fusion for robust multimedia classification. Multimedia Tools and Applications, 80(14), 21885-21898.

• Zhou, J., Zhang, Q., Zhang, B., & Chen, X. (2019). TongueNet: a precise and fast tongue segmentation system using U-Net with a morphological processing layer. Applied Sciences, 9(15), 3128.

• Zhou, J., & Zhang, B. (2019). Collaborative representation using non-negative samples for image classification. Sensors, 19(11), 2609.

荣誉奖励

上海市海外高层次人才，上海市人力资源和社会保障局，2025