Biography
Hongmin Cai , Vice Dean of the School of Future Technology at South China University of Technology, is a Professor and Doctoral Supervisor at the School of Future Technology and the School of Computer Science and Engineering, as well as a Xinghua Distinguished Scholar. He currently serves as Deputy Director of the Bioinformatics and Artificial Life Committee of the Chinese Association for Artificial Intelligence, and is an IET Fellow and IEEE Senior Member. He is also an Editorial Board Member of the international journal IEEE Transactions on Emerging Topics in Computational Intelligence. With long-term expertise in AI-powered data analysis for biomedicine, his research findings have been published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence. He has led over 10 national-level research projects, including the National Key R&D Program of China and the National Natural Science Foundation of China Outstanding Youth Science Fund. In recognition of his contributions, he was awarded the First Prize of the 2024 Guangdong Provincial Science and Technology Progress Award.
Personal Website
https://www2.scut.edu.cn/bioinformatics/sysPIjs/list.htm
Education
Sep 2003 – Sep 2007: Ph.D. in Philosophy (Applied Mathematics), The University of Hong Kong
Sep 2001 – Jul 2003: M.S. in Science (Fundamental Mathematics), Harbin Institute of Technology
Sep 1997 – Jul 2001: B.S. in Science (Mathematics and Information Science), Harbin Institute of Technology
Work Experience
Sep 2016 – Present: South China University of Technology, School of Future Technology, Administrative Vice Dean, Professor, Doctoral Supervisor
Jun 2019 – Oct 2019: Kyoto University (Japan), Institute of Chemical Research, Visiting Professor
Sep 2016 – Nov 2023: South China University of Technology, School of Computer Science and Engineering, Professor, Doctoral Supervisor
Mar 2012 – Sep 2016: South China University of Technology, School of Computer Science and Engineering, Associate Professor
Sep 2008 – Mar 2012: Sun Yat-sen University, School of Information Science and Technology, Lecturer, Master's Supervisor
Jun 2006 – Dec 2006: University of Pennsylvania, Section of Biomedical Engineering, Visiting Scholar
Apr 2005 – Oct 2005: Harvard University, Center for Bioinformatics, Visiting Scholar
Research Projects
Source: National Natural Science Foundation of China (NSFC) Outstanding Youth Science Fund
Title: Key Technologies for Unsupervised Clustering of Multi-Omics Data
Principal Investigator (PI): Cai Hongmin
Funding: RMB 4 million
Period: Jan 2024 - Dec 2028
Source: NSFC-Guangdong Joint Fund Key Project
Title: Intelligent Analysis Methods for Multi-Modal Medical Imaging in Brain Disorders
Principal Investigator (PI): Cai Hongmin
Funding: RMB 2.6 million
Period: Jan 2022 - Dec 2025
Source: Ministry of Science and Technology (MOST) Key R&D Program - International Cooperation in Key Regions
Title: Theory and Application Research on Multi-Scale Bioinformatics Data Integration and Analysis
Principal Investigator (PI): Cai Hongmin
Funding: RMB 3 million
Period: Jan 2022 - Dec 2024
Source: Guangdong Provincial Science and Technology Plan - International S&T Cooperation Key Project
Title: Theory of Multi-Scale Bioinformatics Data Integration and Its Application in AI-Assisted Diagnosis Industry
Principal Investigator (PI): Cai Hongmin
Funding: RMB 1 million
Period: Jan 2023 - Dec 2024
Source: Guangzhou Key R&D Program
Title: Research on Key Technologies for Multi-Source Heterogeneous Data and Cross-Domain Knowledge Aggregation and Their Demonstrative Applications
Principal Investigator (PI): Cai Hongmin
Funding: RMB 5 million
Period: Apr 2022 - Mar 2025
Courses Taught
Discrete Mathematics, Analysis of Algorithms, Data Structures, Machine Learning, Optimization, Advanced Computational Methods
Selected Publications
[1] Y. Hu, E. Guo, Z. Xie, X. Liu, and H. Cai*. Robust Multi-view Clustering through Partition Integration on Stiefel Manifold. IEEE Transactions on Knowledge and Data Engineering (2023). DOI: 10.1109/TKDE.2023.3253244.(CAS Tier 2, JCR Q1, IF: 8.9)
[2] H. Cai, B. Zhang, J. Li, B. Hu, and J. Chen. Unsupervised Dual Hashing Coding (UDC) on Semantic-wise Tagging and Sample-wise Content for Cross-modal Retrieval. IEEE Transactions on Multimedia (2023).(CAS Tier 1, JCR Q1, IF: 7.3)
[3] B. Zhang, Y. Zhang, J. Li, J. Chen, T. Akutsu, Y. Cheung, and H. Cai*. Unsupervised Dual Deep Hashing with Semantic-Index and Content-Code for Cross-Modal Retrieval. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023). (CAS Tier 1, JCR Q1, IF: 23.6)
[4] H. Cai, L. Zhu, Y. Liao, J. Song*. Improving cancer survival prediction via graph convolutional neural networks learning on protein-protein interaction networks. IEEE Journal of Biomedical and Health Informatics, (2023).(CAS Tier 1, JCR Q1, IF: 7.7)
[5] M. Lin, X. Zhang, R. You, Y. Liu, H. Cai, et. al, T. Liu, M. Chen. Evolutionary route of nasopharyngeal carcinoma metastasis and its clinical significance. Nature Communications 14.1 (2023): 610.(CAS Tier 1, JCR Q1, IF: 16.6)
[6] G Tao, H Li, J Huang, C Han, J Chen, G Ruan, W Huang, Y Hu, T Dan, et. al, H. Cai*. SeqSeg: A sequential method to achieve nasopharyngeal carcinoma segmentation free from background dominance. Medical Image Analysis 78 (2022): 102381.(CAS Tier 1, JCR Q1, IF: 10.9)
[7] J. Li, J. Chen, F. Qi, T. Dan, W. Weng, B. Zhang, H. Yuan, and H. Cai*. Two-dimensional unsupervised feature selection via sparse feature filter. IEEE Transactions on Cybernetics (2022). DOI: 10.1109/TCYB.2022.3162908.(CAS Tier 1, JCR Q1, IF: 11.8)
[8] Y. Li, T. Dan, H. Li, J. Chen, H. Peng, L. Liu, H. Cai*. NPCNet: jointly segment primary nasopharyngeal carcinoma tumors and metastatic lymph nodes in MR images. IEEE Transactions on Medical Imaging 41.7 (2022): 1639-1650.(CAS Tier 1, JCR Q1, IF: 10.6)
[9] H. Peng, Y. Hu, J. Chen, H. Wang, Y. Li, and H. Cai*. Integrating tensor similarity to enhance clustering performance. IEEE Transactions on Pattern Analysis and Machine Intelligence 44.5 (2020): 2582-2593.(CAS Tier 1, JCR Q1, IF: 23.6)
Selected Invited Talks
[1] Nanhai Bioinformatics Forum 2023, Chengmai, Hainan, China, Plenary Lecture.
[2] The 12th National Conference on Bioinformatics and Systems Biology, Qingdao, China, Plenary Lecture.
[3] Frontier Interdisciplinary Symposium on Artificial Intelligence, Big Data and Bioinformatics, Changsha, China, Invited Plenary Lecture.
[4] Symposium on Innovative Practices in Healthcare under the Digital Background, Zhuhai, China, Invited Plenary Lecture.
[5] “Research on the Theory and Application of Integrated Analysis of Small SampleData from Multiple Sources”, International Conference on Bioscience, Biochemistry and Bioinformatics, 2022, Tokyo, Japan, keynote speech;
[6] “Manifold Learning in Detecting the Transitions of Dynamic Functional Connectivities Boosts Brain State-Specific Recognition”, International Symposium on Biomedical Imaging, 2022, Online;
[7] “Tensor Spectral Clustering for High-dimension-low-sample-size Data Clustering”, International Symposium on Artificial Intelligence for Medicine Sciences, 2021, Zhengzhou, China, keynote speech;
[8] “Research on the Theory and Application of Integrated Analysis of Small SampleData from Multiple Sources”, International Symposium on Artificial lntelligence for Medical Sciences, 2021, Xi’ an, China, keynote speech.
