I am an associate professor and master’s supervisor at Nanjing Normal University, with a primary research focus on machine learning and data mining.

I received my bachelor’s and master’s degrees from Southeast University, my Ph.D. from Tongji University, and completed a postdoctoral fellowship at Southeast University. I am a visiting scholar sponsored by the China Scholarship Council (CSC). I serve as a committee member of the Visual Big Data Committee of the Chinese Society for Image and Graphics (CSIG-BVD). I have led several projects including a National Natural Science Foundation of China (NSFC) Project and a Youth Project, a sub-project of a key research and development plan project funded by the Science and Technology Department of Jiangsu Province, a China Postdoctoral Science Foundation project, and a Jiangsu Higher Education Science Foundation project.

As a first author or corresponding author, I have published over 20 papers in top-tier SCI journals and conferences such as IEEE Transactions on Knowledge and Data Engineering (TKDE), IEEE Transactions on Cybernetics (TCYB), Pattern Recognition (PR), Knowledge-Based Systems (KBS), PRCV, KSEM, IJCNN, ADMA, PRICAI, among others. I served as a session chair at PRICAI 2018 and have reviewed articles for multiple SCI journals and international conferences including Pattern Recognition and Neurocomputing. I was awarded the ACM Nanjing Chapter’s Rising Star Award in 2021.

✨ Research Interests

• Machine learning
• Label distribution learning and Label enhancement
• Open-world learning
• Image classification

🔥 News

• 2025.04: 🎉 One paper is accepted by IJCAI 2025(CCF A).
• 2025.04: 🎉 One paper is accepted by KBS(中科院一区TOP).
• 2024.11: 🎉 Congratulations to Xuzilong for being awarded the China National Scholarship for Postgraduate Students!
• 2024.07: 🎉 One paper is accepted by KBS(中科院一区TOP).
• 2024.06: 🎉 One paper is accepted by PR(CCF B 中科院一区TOP).

📝 Publications

🎙 Nearest Research Papers

KBS 2025

RG4LDL: Renormalization Group for Label Distribution Learning, Chao Tan*, Sheng Chen, Jiaxi Zhang, Zilong Xu, Xin Geng, Genlin Ji(中科院一区TOP)
Keywords: Label distribution learning, Unsupervised neural network, Renormalization group, Restricted Boltzmann machine

KBS 2024

Efficient Representation Learning for Generalized Category Discovery
Zilong Xu, Chao Tan*, Jiaxi Zhang, Anning Song, Genlin Ji(中科院一区TOP)
Keywords: Open-world Learning, Generalized category discovery, Image classification

PR 2024

Label enhancement via manifold approximation and projection with graph convolutional network
Chao Tan*, Sheng Chen, Xin Geng, Yunyao Zhou, Genlin Ji(CCF B 中科院一区TOP)
Keywords: Multi-label classification, Label distribution learning, Manifold learning

🎙 All Publications

You can also find my articles on my Google Scholar profile.

📰 Journal Papers

• 2025 Knowledge-based Systems RG4LDL: Renormalization Group for Label Distribution Learning, Chao Tan*, Sheng Chen, Jiaxi Zhang, Zilong Xu, Xin Geng, Genlin Ji(中科院一区TOP)
• 2024 Knowledge-based Systems Efficient Representation Learning for Generalized Category Discovery, Zilong Xu, Chao Tan*, Jiaxi Zhang, Anning Song, Genlin Ji(中科院一区TOP)
• 2024 Pattern Recognition Label enhancement via manifold approximation and projection with graph convolutional network, Chao Tan*, Sheng Chen, Xin Geng, Yunyao Zhou, Genlin Ji(CCF B 中科院一区TOP)
• 2023 Concurrency and Computation: Practice and Experience Multi‐label enhancement manifold learning algorithm for vehicle video, Chao Tan*, Genlin Ji, Xiaoqian Zeng
• 2023 Pattern Recognition A novel label enhancement algorithm based on manifold learning, Chao Tan*, Sheng Chen, Xin Geng, Genlin Ji(CCF B 中科院一区TOP)
• 2023 Pattern Recognition A label distribution manifold learning algorithm, Chao Tan*, Sheng Chen, Xin Geng, Genlin Ji(CCF B 中科院一区TOP)
• 2022 IEEE Transactions on Knowledge and Data Engineering A novel probabilistic label enhancement algorithm for multi-label distribution learning, Chao Tan, Sheng Chen, Genlin Ji, Xin Geng*(CCF A 中科院一区TOP)
• 2022 IEEE Transactions on Cybernetics Multilabel distribution learning based on multioutput regression and manifold learning, Chao Tan*, Sheng Chen, Genlin Ji, Xin Geng(CCF B 中科院一区TOP)
• 2020 Tsinghua Science and Technology LTSA-LE: A local tangent space alignment label enhancement algorithm, Chao Tan*, Genlin Ji, Richen Liu, Yanqiu Cao(中科院二区)
• 2019 Journal of Imaging Science & Technology Sketch-Based Slice Interpretative Visualization for Stratigraphic Data, Richen Liu, Liming Shen, Xueyi Chen, Genlin Ji, Bin Zhao, Chao Tan, Mingjun Su
• 2019 Visual Informatics A survey of multi-space techniques in spatio-temporal simulation data visualization, Xueyi Chen, Liming Shen, Ziqi Sha, Richen Liu, Siming Chen, Genlin Ji, Chao Tan
• 2019 Tsinghua Science and Technology LKLR: A local tangent space-alignment kernel least-squares regression algorithm, Chao Tan*, Genlin Ji(中科院二区)
• 2017 Journal of Computer Research and Development Self-adaptive Streaming Big Data Learning Algorithm Based on Incremental Tangent Space Alignment, Chao Tan*, Genlin Ji, Bin Zhao(CCF T1)
• 2017 Concurrency and Computation: Practice and Experience Semisupervised local preserving embedding algorithm based on maximum margin criterion for large‐scale data streams, Chao Tan*, Genlin Ji
• 2017 Concurrency and Computation: Practice and Experience Semi-supervised incremental feature extraction algorithm for large-scale data stream, Chao Tan*, Genlin Ji
• 2014 Pattern Recognition and Artificial Intelligence Multi-sample incremental manifold learning algorithm based on Isogonal mapping, Chao Tan, Jihong Guan*, Shuigeng Zhou(CCF T2)
• 2013 CAAI Transactions on Intelligent Systems Incremental and evolutionary manifold learning: a survey, Chao Tan, Jihong Guan*, Shuigeng Zhou(CCF T2)

💼 Conference Papers

• 2024 International Joint Conference on Neural Networks Imbalanced Label Enhancement Based on Variational Information Bottleneck, Anning Song, Chao Tan*, Jiaxi Zhang, Zilong Xu
• 2023 Chinese Conference on Pattern Recognition and Computer Vision Leveraging Data Correlations for Skin Lesion Classification, Junzhao Hao, Chao Tan*, Qinkai Yang, Jing Cheng, and Genlin Ji
• 2023 Eleventh International Conference on Advanced Cloud and Big Data Label Distribution-based Open-world Semi-supervised Learning, Qinkai Yang, Chao Tan, Junzhao Hao, Genlin Ji
• 2023 26th International Conference on Computer Supported Cooperative Work in Design Privileged Label Enhancement with Adaptive Graph, Qin Qin, Chao Tan*, Chong Li, Genlin Ji
• 2022 Tenth International Conference on Advanced Cloud and Big Data Label Enhancement with Sample Correlation via Sparse Representation, Xiaoqian Zeng, Qin Qin, Chao Tan*, Genlin Ji
• 2022 Pacific Rim International Conference on Artificial Intelligence Label Enhancement Using Inter-example Correlation Information, Chong Li, Chao Tan*, Qin Qin, Genlin Ji
• 2021 Ninth International Conference on Advanced Cloud and Big Data Label Enhancement with Sample Correlations via Low-dimensional Feature Representation, Xiaoqian Zeng, Zhen Xu, Chao Tan*, Genlin Ji
• 2020 Eighth International Conference on Advanced Cloud and Big Data Label Enhancement Manifold Learning Algorithm for Multi-label Image Classification, Chao Tan*, Genlin Ji
• 2018 15th Pacific Rim International Conference on Artificial Intelligence DKE-RLS: a manifold reconstruction algorithm in label spaces with double kernel embedding-regularized least square, Chao Tan*, Genlin Ji
• 2016 International Conference on Advanced Cloud and Big Data SSLPE: A Semi-Supervised Local Preserving Embedding Algorithm, Chao Tan*, Genlin Ji
• 2016 Cloud Computing and Security: Second International Conference A manifold learning algorithm based on incremental tangent space alignment, Chao Tan*, Genlin Ji
• 2015 Third International Conference on Advanced Cloud and Big Data SLFE: A New Semi-supervised Local Feature Extraction Algorithm, Chao Tan*, Genlin Ji, Bin Zhao
• 2015 Machine Learning and Data Mining in Pattern Recognition IKLTSA: An incremental kernel LTSA method, Chao Tan, Jihong Guan*, Shuigeng Zhou
• 2013 Knowledge Science, Engineering and Management A nonlinear dimension reduction method with both distance and neighborhood preservation, Chao Tan, Chao Chen, Jihong Guan*
• 2012 Advanced Data Mining and Applications: 8th International Conference A new manifold learning algorithm based on incremental spectral decomposition, Chao Tan, Jihong Guan*
• 2012 12th Pacific Rim International Conference on Artificial Intelligence A feature space alignment learning algorithm, Chao Tan, Jihong Guan*

🖥 Projects

• 2025 - 2028, Research on Incremental Label Distribution Learning in Open-environment, National Natural Science Foundation of China
• 2023 - 2026, Key technologies of big data governance and analysis for national audit and research and development, Jiangsu Province science and technology plan key research and development plan project(sub topic)
• 2018 - 2020, Research on incremental feature extraction algorithms of high dimensional big data streams, National Natural Science Foundation of China Youth Project
• 2017 - 2019, Research on incremental manifold learning optimization algorithm for big data streams, China Postdoctoral Science Foundation
• 2017 - 2018, Research on the incremental adaptive manifold learning algorithm for big data flow, the open project foundation of Shanghai Key Laboratory of Intelligent Information Processing, Fudan University
• 2015 - 2017, Incremental Semi-supervised Learning Algorithms for Big Data Stream, Natural Science Research of Jiangsu Higher Education Institutions

🏅 Honors and Awards

🎖 Academic Title:

• Member of CSIG-BVD Special Committee
• Member, CSIG Women Authors Committee
• Member of the China Computer Federation
• Member of the Jiangsu Assocation of Artificial Intelligence
• PRICAI 2018 session chair
• PC Member of the International Conference on Advanced Cloud and Big Data

🎖 Awards:

• 2021 ACM China Council Nanjing Chapter Rising Star Award
• CBD2016 Best Paper Award