【个人简介】
张越,广东技术师范大学教授,博士,硕士生导师。中国生物信息学学会会员,广东省计算机学会会员,国家自然科学基金通讯评审专家。主要研究专注于大数据科学应用、机器学习、图像处理及智能优化算法研究。近年来发表多篇论文,均被SCI,EI检索。主持和参与国家自然科学基金面上项目,科技部重点研发计划、广东省自然科学基金、广州市民生科技攻关计划项目、广东省普通高校重点领域专项等科研课题9项。
【教育背景】
博士学位
【工作经历】
2004.3-2019.12:暨南大学学院
2020.1-至今: 广东技术师范大学计算机学院
【学科领域】
主要从事数据挖掘、生物信息等领域的算法设计和分析研究。
【主讲课程】
《运筹学》 、《线性代数》 、《概率论和数理统计》 、《矩阵论》(研究生)
【项目课题】
[1]科技部国家重点研发计划子课题项目,多尺度生物信息学整合分析理论和应用研究,2022.05-2025.05,60万,在研,主持
[2]国家自然科学基金面上项目,面向多组学数据的深度聚类理论与应用研究,2022/01-2024/12,61万,在研,主持
[3]国家自然科学基金,细粒度隐性关联知识发现及其可视化探索方法研究,2021.08-2025.12,56万,在研,参加
[4]广东省普通高校重点领域专项,面向鼻咽癌诊断的机器学习预测方法研究,2021/01-2023/12,50万,在研,主持
[5]广东省高等学校珠江学者岗位计划资助项目,基于异构传感与人工智能的主动健康管理研究及应用,2021.06-2023.05,80万,在研,参加
[6]广东省自然科学基金青年项目,2018030310185,面向单细胞数据测序的基因变异分析理论和应用,2018/01-2020/12,10万,已结题,主持
[7]华南肿瘤学国家重点实验室开放课题,HN2018-09,鼻咽肿瘤单细胞基因组变异分析及亚克隆群发现,2018/01-2018/12,5万,已结题,主持
[8]广州市民生科技攻关计划项目,鼻咽癌大数据云端诊疗分析系统,2018/01-2021/12, 200万,在研,参加
[9]广东技术师范大学人才引进计划,基于现代测序技术的基因组变异查找理论和算法,2020/01-2023/12,在研,主持
[10]暨南大学珠海校区科研启动计划(理工类),单细胞测序数据应用,2018/01-2021/12,3万,在研,主持
【主要成果】
1.Yue Zhang, Sirui Yang, Weitian Huang, Chang-Dong Wang, Hongmin Cai, Unified Representation Learning for Multi-view Clustering by Between/Within View Deep Majorization, IEEE Transactions on Emerging Topics in Computational Intelligence, 2023.
2.Yue Zhang, Yuqing Hu, Na Han, Aqing Yang, Xiaoyong Liu, Hongmin Cai, A survey of drug-target interaction and affinity prediction methods via graph neural networks, Computers in Biology and Medicine, 2023.
3.Yue Zhang, Yuqing Hu, Huihui Li, Xiaoyong Liu, Drug-protein interaction prediction via variational autoencoders and attention mechanisms, Frontiers in Genetics, 2022.
4.Wuxiu Quan, Yu Hu, Tingting Dan, Junyu Li,Yue Zhang*, Hongmin Cai, Weakly-supervised Instance Co-segmentation via Tensor-based Salient Co-peak Search, Frontiers of Computer Science, 2022.
5.Zhuohui Wei,Yue Zhang, Wanlin Weng, Jiazhou Chen, Hongmin Cai, Survey and comparative assessments of computational multi-omics integrative methods with multiple regulatory networks identifying distinct tumor compositions across pan-cancer data sets, Briefings in Bioinformatic, 2021.
6.Dandan Lu,Yue Zhang, Ling Zhang, Haiyan Wang, Wanlin Weng, Li Li, Hongmin Cai, Methods of privacy-preserving genomic sequencing data alignments, Briefings in Bioinformatic, 2021.
7.Zhichao Zhou, Yu Hu,Yue Zhang, Jiazhou Chen, Hongmin Cai, Multiview Deep Graph Infomax to Achieve Unsupervised Graph Embedding, IEEE Transactions on Cybernetics, 2023.
8.Hongmin Cai, Weitian Huang, Sirui Yang, Siqi Ding,Yue Zhang, Bin Hu, Fa Zhang, Yiu-Ming Cheung, Realize Generative Yet Complete Latent Representation for Incomplete Multi-View Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023.
9.Yue Zhang, Qinjian Huang, Bin Zhang, Shengfeng He , Tingting Dan ,and Hongmin Cai ,Deep Multiview Clustering via Iteratively Self-Supervised Universal and Specific Space Learning,IEEE Transactions on Cybernetics,2168-2275, 2021.
10.Zhuohui Wei,Yue Zhang#,Wanlin Weng,Jiazhou Chen,Hongmin Cai. Survey and comparative assessments of computational multi-omics integrative methods with multiple regulatory networks identifying distinct tumor compositions across pan-cancer data sets. Briefings in Bioinformatic, 2020, bbaa102.
11.Huang Q,Yue Zhang#, Peng H, Dan T, et al. Deep Subspace Clustering to Achieve Jointly Latent Feature Extraction and Discriminative Learning[J], Neurocomputing,2020.
12.Zeng Jingwen, Cai Hongmin, Peng Hong, Wang Haiyan,Zhang Yue*, Akutsu Tatsuya, “Causalcall: Nanopore Basecalling Using a Temporal Convolutional Network”, Frontiers in Genetics,10,2020,1332.
13.Zhang Yue, Yiu-ming Cheung, Bo Xu, and Weifeng Su, “Detecting Copy Number Variants from NGS with Sparse and Smooth Constraints”, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.99, pp.1-9, 2016.
14.Zhang Yue, Yiu-ming Cheung, and Weifeng Su, “A Total-variation Constrained Permutation (TCP)Model for Revealing Common Copy Number Patterns”, Scientific Report, 1(7),2017,9666-9674.
15.Xiaoping Cheng, Hongmin Cai*,Yue Zhang, Ping He, and Runtiao Tian,“Combination of effective machine learning techniques and chemometric analysis for evaluation of Bupleuri Radix through high-performance thin-layer chromatography”,Anal. Methods, 2013,5, 6325-6330).
16.Zhang Yue, Xue Xiaoping, On stability condition of a class of delay cellular neural networks, Journal of Natural Science of Heilongjiang University, Vol.23(3), pages. 415-417,2006 .
17.Zhang Yue, Xiaoyin Xu, Hongmin Cai, “A New Nonlinear Diffusion Method to Improve Image Quality”, ICIP, pages.329-332 ,2007(EI会议,CCF-B类).
【联系方式】
邮箱:zhangyue@gpnu.edu.cn