Le OUYANG, Professor

Professor at Shenzhen MSU-BIT University (SMBU).

歐陽(yáng)樂(lè)

深圳北理莫斯科大學(xué)工程系教授、博士生導(dǎo)師

He received the PhD degree from Sun Yat-sen University in 2015. He is a Senior Member of the China Computer Federation (CCF) and has received the Guangdong Outstanding Young Scholar, the Shenzhen Excellent Young Scholar, and has been selected for the Guangdong Pearl River Talent Program. He has led three NSFC projects. He has published over 70 SCI papers in top-tier journals such as Nature Biotechnology, IEEE TCYB, Bioinformatics, and Briefings in Bioinformatics. He serves as Associate Editor for IEEE Transactions on Computational Biology and Bioinformatics, and as an Editorial Board Member for Neural Networks, and serves as a reviewer for journals such as Nature Communications, Nucleic Acids Research, Genome Biology, Advanced Science, IEEE TPAMI, and IEEE TNNLS. He is also a program committee member for major international conferences, including AAAI, IJCAI, ICML, NIPS, and ICLR. Additionally, he is a committee member of the Professional Committee of Bioinformatics of the China Computer Federation (CCF), the Professional Committee of Bioinformatics and Artificial Life of the Chinese Association for Artificial Intelligence (CAAI), the Professional Committee of Intelligent Health and Bioinformatics of the Chinese Association of Automation (CAA), and a board member of the Guangdong Bioinformatics Society.

Research interests: Machine learning, Bioinformatics

2015年在中山大學(xué)獲得博士學(xué)位，2013-2014年在新加坡南洋理工大學(xué)計(jì)算機(jī)科學(xué)系交流訪(fǎng)問(wèn)，2015-2016年在香港城市大學(xué)電子工程系從事博士后研究。主要從事機(jī)器學(xué)習(xí)、數(shù)據(jù)挖掘和生物信息學(xué)等領(lǐng)域的科研和教學(xué)工作。CCF高級(jí)會(huì)員，廣東省杰青、深圳市優(yōu)青獲得者，入選廣東省珠江人才計(jì)劃。主持國(guó)家自然科學(xué)基金3項(xiàng)、廣東省自然科學(xué)基金3項(xiàng)、市級(jí)項(xiàng)目4項(xiàng)，已在 Nature Biotechnology、IEEE TCYB、Bioinformatics、Briefings in Bioinformatics 等國(guó)際期刊發(fā)表 SCI 論文 70 余篇。擔(dān)任國(guó)際權(quán)威期刊IEEE Transactions on Computational Biology and Bioinformatics副主編、Neural Networks編委，以及Nature Communications、Nucleic Acids Research、Genome Biology、Advanced Science、IEEE TPAMI、IEEE TNNLS等重要刊物審稿人，AAAI、IJCAI、ICML、NIPS、ICLR等國(guó)際學(xué)術(shù)會(huì)議程序委員會(huì)委員。擔(dān)任中國(guó)計(jì)算機(jī)學(xué)會(huì)生物信息學(xué)專(zhuān)委會(huì)委員、中國(guó)人工智能學(xué)會(huì)生物信息學(xué)與人工生命專(zhuān)委會(huì)委員、中國(guó)自動(dòng)化學(xué)會(huì)智能健康與生物信息專(zhuān)委會(huì)委員、廣東省生物信息學(xué)會(huì)理事。

研究方向：機(jī)器學(xué)習(xí)、生物信息學(xué)和健康醫(yī)療大數(shù)據(jù)

研究生招生方向：

博士：計(jì)算機(jī)科學(xué)與技術(shù)

碩士：計(jì)算機(jī)科學(xué)與技術(shù)、計(jì)算機(jī)技術(shù)、人工智能

Selected Papers

[1] Weiming Yu, Zerun Lin, Miaofang Lan, Le Ou-Yang*, GCLink: a graph contrastive link prediction framework for gene regulatory network inference, Bioinformatics, 41(3): btaf074, 2025.

[2] Zibo Huang, Xinrui Weng, Le Ou-Yang*, GFLearn: Generalized Feature Learning for Drug-Target Binding Affinity Prediction, IEEE Journal of Biomedical and Health Informatics, 2025, in press.

[3] Yujie Chen, Wenhui Wu*, Le Ou-Yang*, Ran Wang, Sam Kwong, GRESS: Grouping Belief-Based Deep Contrastive Subspace Clustering, IEEE Transactions on Cybernetics, 55(1): 148-160, 2025.

[4] Fuqun Chen, Guanhua Zou, Yongxian Wu, Le Ou-Yang*, Clustering single-cell multi-omics data via graph regularized multi-view ensemble learning, Bioinformatics, 40(4): btae169, 2024.

[5] Zerun Lin, Le Ou-Yang*, Inferring gene regulatory networks from single-cell gene expression data via deep multi-view contrastive learning, Briefings in Bioinformatics, 24(1): bbac586, 2023.

[6] Youlin Zhan, Jiahan Liu, Le Ou-Yang*, scMIC: A Deep Multi-Level Information Fusion Framework for Clustering Single-Cell Multi-Omics Data, IEEE Journal of Biomedical and Health Informatics, 27(12): 6121-6132, 2023.

[7] Wenhui Wu, Yujie Chen, Ran Wang, Le Ou-Yang*, Self-representative kernel concept factorization, Knowledge-Based Systems, 259: 110051, 2023.

[8] Guanhua Zou, Yilong Lin, Tianyang Han, Le Ou-Yang*, DEMOC: a deep embedded multi-omics learning approach for clustering single-cell CITE-seq data, Briefings in Bioinformatics, 23(5): bbac347, 2022.

[9] Le Ou-Yang, Fan Lu, Zi-Chao Zhang, Min Wu, Matrix factorization for biomedical link prediction and scRNA-seq data imputation: an empirical survey, Briefings in Bioinformatics, 23(1): bbab479, 2022.

[10] Le Ou-Yang, Dehan Cai, Xiao-Fei Zhang, Hong Yan, WDNE: an integrative graphical model for inferring differential networks from multi-platform gene expression data with missing values, Briefings in Bioinformatics, 22(6): bbab086, 2021.

[11] Xiao-Fei Zhang, Le Ou-Yang*, Ting Yan, Xiaohua Tony Hu, Hong Yan, A joint graphical model for inferring gene networks across multiple subpopulations and data types, IEEE Transactions on Cybernetics, 51(2): 1043-1055, 2021.

[12] Le Ou-Yang, Xiao-Fei Zhang, Hong Yan, Sparse regularized low-rank tensor regression with applications in genomic data analysis, Pattern Recognition, 107: 107516, 2020.  

獲獎(jiǎng)信息：

2011年獲中山大學(xué)優(yōu)秀研究生

2013年獲博士研究生國(guó)家獎(jiǎng)學(xué)金

2017年獲深圳市海外高層次人才（孔雀計(jì)劃）C類(lèi)

2018年獲南山區(qū)“領(lǐng)航人才”C類(lèi)

2018年獲廣東省珠江人才計(jì)劃青年拔尖人才

2022年獲騰訊益友獎(jiǎng)“優(yōu)秀班主任”

2022年獲廣東省大學(xué)生創(chuàng)新創(chuàng)業(yè)訓(xùn)練計(jì)劃優(yōu)秀指導(dǎo)教師

2023年獲廣東省大學(xué)生計(jì)算機(jī)設(shè)計(jì)大賽優(yōu)秀指導(dǎo)教師

指導(dǎo)學(xué)生獲獎(jiǎng)情況：

指導(dǎo)學(xué)生獲得美國(guó)大學(xué)生數(shù)學(xué)建模競(jìng)賽一等獎(jiǎng)3項(xiàng)

指導(dǎo)學(xué)生獲得美國(guó)大學(xué)生數(shù)學(xué)建模競(jìng)賽二等獎(jiǎng)5項(xiàng)

指導(dǎo)學(xué)生獲得中國(guó)大學(xué)生計(jì)算機(jī)設(shè)計(jì)大賽一等獎(jiǎng)1項(xiàng)、二等獎(jiǎng)4項(xiàng)、三等獎(jiǎng)2項(xiàng)

指導(dǎo)學(xué)生獲得2019年mathorcup高校數(shù)學(xué)建模挑戰(zhàn)賽二等獎(jiǎng)1項(xiàng)

指導(dǎo)國(guó)家級(jí)大學(xué)生創(chuàng)新創(chuàng)業(yè)訓(xùn)練計(jì)劃3項(xiàng)

指導(dǎo)省級(jí)大學(xué)生創(chuàng)新創(chuàng)業(yè)訓(xùn)練計(jì)劃4項(xiàng)

指導(dǎo)學(xué)生獲得首屆“興智杯”全國(guó)人工智能創(chuàng)新應(yīng)用大賽三等獎(jiǎng)1項(xiàng)

指導(dǎo)學(xué)生獲得首屆“興智杯”全國(guó)人工智能創(chuàng)新應(yīng)用大賽行業(yè)賦能專(zhuān)題賽一等獎(jiǎng)1項(xiàng)

指導(dǎo)學(xué)生獲得中國(guó)電子學(xué)會(huì)2023首屆大學(xué)生算法大賽三等獎(jiǎng)2項(xiàng)

研究生招生：

招收有志于從事科學(xué)研究的學(xué)生（學(xué)術(shù)型和專(zhuān)業(yè)型均可）

要求：

a) 高等數(shù)學(xué)、線(xiàn)性代數(shù)、數(shù)值分析、概率論與數(shù)理統(tǒng)計(jì)等課程基礎(chǔ)扎實(shí)；

b) 至少精通兩門(mén)編程語(yǔ)言：Matlab、Python、C++、Java；

c) 英語(yǔ)的聽(tīng)說(shuō)讀寫(xiě)能力強(qiáng)，有較強(qiáng)的英文閱讀和寫(xiě)作能力；

d) 對(duì)研究方向感興趣，對(duì)科學(xué)研究有熱情，不怕吃苦、不怕失敗、做事認(rèn)真負(fù)責(zé)?；鞂W(xué)位者請(qǐng)勿聯(lián)系。

注：從事科學(xué)研究并不指畢業(yè)后只是在高校和研究所工作，也指愿意畢業(yè)后去著名公司從事研發(fā)工作或研究院工作、或出國(guó)留學(xué)繼續(xù)攻讀博士學(xué)位等。

本科生招生：

招收有志于繼續(xù)攻讀碩士研究生或有志于在本科/碩士階段后攻讀國(guó)外大學(xué)碩士/博士學(xué)位的1-3年級(jí)本科生。

要求：有志于在未來(lái)從事機(jī)器學(xué)習(xí)和生物信息學(xué)方向?qū)W術(shù)研究的學(xué)生，尤其側(cè)重于健康醫(yī)療大數(shù)據(jù)和機(jī)器學(xué)習(xí)算法研究。要求數(shù)學(xué)和編程相關(guān)課程學(xué)業(yè)成績(jī)較高。能夠把課余的50～70%的時(shí)間全部用于科研中，只有集中精力做好一件事才能做好。

修讀或自修以下課程：線(xiàn)性代數(shù)、概率統(tǒng)計(jì)、Matlab/Python、多元統(tǒng)計(jì)分析、矩陣論。