工学博士，山东大学教授，博/硕士生导师，山东省泰山学者青年专家。主要研究领域人工智能、大数据分析与挖掘及其在生物医学等多领域的应用研究。在国内外知名期刊和会议（IEEE TKDE, TNNLS, TCYB, NAR, Bioinformatics, BiB,计算机学报,软件学报,电子学报,KDD,AAAI等）发表论文100余篇，Google引用2900余次，H-index=29。主持/完成国家重点研发计划课题1项（423万），国家自然科学基金5项（重点项目课题1项，面上3项，青年1项），省部级科技项目和阿里巴巴、华为等企业项目10余项，获重庆市自然科学三等奖（2020）/科技进步三等奖（2019）各1项，山东计算机学会自然科学一等奖1项（2023），山东省人工智能自然科学二等奖1项（2024）。

现任《北京建筑大学学报》编委；常年受邀担任IJCAI, AAAI, ECML, SDM和BIBM等人工智能/机器学习/数据挖掘等领域国际国内重要会议程序委员会委员（Senior/Program Committee），Nature子刊，TNNLS，TCYB，TII， NAR，Bioinformatics，BiB，自动化学报，计算机学报，电子学报等多个国内外著名期刊审稿人。现任中国计算机学会高级会员（人工智能与模式识别专委会执行委员、生物信息学专委会执行委员），中国人工智能学会会员（生物信息学与人工生命专委会委员，机器学习专委会委员），IEEE/ACM会员，中国生物工程学会会员（计算生物学与生物信息学专委会委员）。科技部，国家自然科学基金，加拿大等国科技项目和多个省市科技项目（奖励）函（会）评专家。

 研究团队：智能数据工程与分析实验室（www.sdu-idea.cn）

   招生信息(2025)(*表示名额尚未确定)： 

(1)学术型博士: 软件工程（0),人工智能(0)

(2)专业型博士: 电子信息（0）

(3)学术型硕士: 软件工程（1），人工智能（1）

(4)专业型硕士: 电子信息-软件工程方向（1）,电子信息-人工智能方向（1）

硕士生招生说明：学院一般在秋季学期初公布导师各个类别的年度招生名额，有意向的同学在确认被录取后，请尽快联系我是否还有对应类别名额。

博士生招生说明：建议在报考之前与我联系(申请考核为主)！

代表成果：完整论文列表

期刊论文

[1]. Jiaxuan Liang, Jun Wang*, Guoxian Yu, Carlotta Domeniconi, Xiangliang Zhang, Maozu Guo. Gradient-based Local Causal Structure Learning. IEEE Transactions on Cybernetics (CCF B,一区top期刊, IF=19.118) ,  2024，54(1): 486-495.

[2]. Jun Wang, Xing Wang, Guoxian Yu*, Carlotta Domeniconi, Zhiwen Yu, Zili Zhang. Discovering Multiple Co-Clusterings with Matrix Factorization, IEEE Transactions on Cybernetics (CCF B,一区top期刊, IF=19.118), 2021, 51(7): 3576-3587.

[3]. Guoxian Yu, Yuehui Wang, Jun Wang*, Carlotta Domeniconi, Maozu Guo, Xiangliang Zhang. Attributed Heterogeneous Network Fusion via Collaborative Matrix Tri-factorization, Information Fusion (CCF B,一区top期刊, IF=17.564), 2020, 63: 153-165.

[4]. Yunfeng Zhao, Guoxian Yu, Jun Wang*, Carlotta Domeniconi, Maozu Guo, Xiangliang Zhang, Lizhen Cui. Personalized Federated Few-Shot Learning. IEEE Transactions on Neural Networks and Learning Systems (CCF B, 一区top期刊，IF=14.255) , In Print.

[5]. Guoxian Yu, Yuying Xing+, Jun Wang*, Carlotta Domeniconi, Xiangliang Zhang. Multi-view Multi-instance Multi-label Active Learning. IEEE Transactions on Neural Networks and Learning Systems (CCF B, 一区top期刊，IF=14.255), 2022, 33(9): 4311-4321.

[6]. Guoxian Yu, Xuanwu Liu, Jun Wang*, Carlotta Domeniconi, Xiangliang Zhang. Flexible Cross-Modal Hashing, IEEE Transactions on Neural Networks and Learning Systems (CCF B, 一区top期刊，IF=14.255), 2022, 33(1): 304-314. 

[7]. Guoxian Yu, Jinzheng Tu, Jun Wang*, Carlotta Domeniconi, Xiangliang Zhang. Active Multi-Label Crowd Consensus, IEEE Transactions on Neural Networks and Learning Systems (CCF B, 一区top期刊，IF=14.255), 2021, 32(4): 1448-1459.

[8]. Jiaxuan Liang, Jun Wang*, Guoxian Yu, Wei Guo, Carlotta Domeniconi, Maozu Guo. Directed Acyclic Graph Learning on Attributed Heterogeneous Network. IEEE Transactions on Knowledge and Data Engineering (CCF A, IF=9.235), 2023,35(9): 10845-10856.

[9]. Guoxian Yu, Xia Chen, Carlotta Domeniconi, Jun Wang*, Zhao Li, Zili Zhang, Xiangliang Zhang. CMAL: Cost-effective Multi-label Active Learning by Querying Subexamples, IEEE Transactions on Knowledge and Data Engineering (CCF A, IF=9.235), 2022, 34(5): 2091-2105.

[10].  Haojiang Tan, Maozu Guo, Jian Chen, Jun Wang*, Guoxian Yu*. HetFCM: Functional co-module discovery by heterogeneous network co-clustering. Nucleic Acids Research (SCI, IF=14.9) , 2024, 52, e62.

[11]. Guoxian Yu, Liangrui Ren, Jun Wang*, Carlotta Domeniconi, Xiangliang Zhang. Multiple Clusterings: Recent Advances and Perspectives. Computer Science Review, (IF=12.9),  2024, 52: 100621.

[12]. Liangrui Ren, Jun Wang*, Zhao Li, Qingzhong Li, Guoxian Yu. scMCs: a framework for single cell multi-omics data integration and multiple clusterings. Bioinformatics (CCF B, IF=6.931), 2023, 39(4): btad133.

[13]. Xingze Wang, Guoxian Yu*, Jun Wang*, Azlan Mohd Zain, and Wei Guo. Lung Cancer Subtype Diagnosis using Weakly-paired Multi-omics Data. Bioinformatics (CCF B, IF=6.931), 2022, 38(22):5092-5099. 

[14]. Guoxian Yu, Keyao Wang, Carlotta Domeniconi, Maozu Guo*, Jun Wang*. Isoform function prediction based on bi-random walks on a heterogeneous network, Bioinformatics (CCF B, IF=6.931), 2020, 36(1): 303-310.

[15]. Jun Wang, Xi Chen, Zhengtian Wu, Maozu Guo and Guoxian Yu*. Cooperative driver pathways discovery by multiplex network embedding. Briefings in Bioinformatics (CCF B, IF=13.994), 2023, 24(3): bbad112.

[16]. Zimo Huang, Jun Wang*, Xudong Lu, Azlan Mohd Zain, Guoxian Yu. scGGAN: single-cell RNA-seq imputation by graph-based generative adversarial n1etwork. Briefings in Bioinformatics (CCF B, IF=13.994), 2023, bbad040.

[17]. Zimo Huang, Jun Wang*, Zhongmin Yan, Maozu Guo. Differentially Expressed Genes prediction by multiple self-attention on epigenetics data. Briefings in Bioinformatics, (CCF B, IF=13.994), 2022, 23(4): bbac117.

[18]. Xin Wang, Xia Cao, Yuantao Feng, Maozu Guo, Guoxian Yu, Jun Wang*. ELSSI: parallel SNP-SNP interactions detection by ensemble multi-type detectors. Briefings in Bioinformatics (CCF B, IF=13.994), 2022, 23(4): bbac213. 

[19]. Jun Wang, Ziying Yang, Carlotta Domeniconi, Xiangliang Zhang, Guoxian Yu*. Cooperative driver pathway discovery via fusion of multi-relational data of genes, miRNAs, and pathways, Briefings in Bioinformatics (CCF B, IF=13.994), 2021, 22(2): 1984-1999.

[20]. Zimo Huang, Jun Wang*, Zhongmin Yan, Lin Wan, Maozu Guo. Differential gene expression prediction by ensemble deep networks on Histone Modification data. IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF B), 2023, 20(1): 340-351. 

[21]. Jun Wang*, Huiling Zhang, Wei Ren, Maozu Guo, Guoxian Yu. EpiMC: Detecting Epistatic Interactions using Multiple Clusterings. IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF B), 2022, 19(1): 243-254. 

[22]. Jun Wang, Long Zhang, An Zeng, Dawen Xia, Jiantao Yu, Guoxian Yu*. DeepIII: Predicting isoform-isoform interactions by deep neural networks and data fusion, IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF B), 2022, 19(4): 2177-2187.

[23]. Guoxian Yu, Qiuyue Huang+, Xiangliang Zhang, Maozu Guo*, Jun Wang*. Tissue Specificity based Isoform Function Prediction. IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF B), 2022, 19(5): 3048-3059.

[24]. Guoxian Yu, Yeqian Yang+, Yangyang Yan+, Maozu Guo, Xiangliang Zhang, Jun Wang*. DeepIDA: predicting isoform-disease associations by data fusion and deep neural networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF B), 2022, 19(4): 2166-2176.

[25]. Ziying Yang, Guoxian Yu, Maozu Guo, Jiantao Yu, Xiangliang Zhang, Jun Wang*. CDPath: Cooperative driver pathways discovery using integer linear programming and Markov clustering, IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF B), 2021, 18(4): 1439-1450.

[26]. Guoxian Yu, Keyao Wang, Guangyuan Fu, Maozu Guo, Jun Wang*. NMFGO: Gene function prediction via nonnegative matrix factorization with Gene Ontology, IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF B), 2020, 36(1): 303-310.

[27]. Lin Jiang, Guoxian Yu, Maozu Guo*, Jun Wang*. Feature selection with missing labels based on label compression and local feature correlation, Neurocomputing (CCF C), 2020, 395: 95-106.

[28]. Long Zhang, Guoxian Yu, Dawen Xia, Jun Wang*. Protein-Protein Interactions Prediction based on Ensemble Deep Neural Networks, Neurocomputing (CCF C), 2019, 324: 10-19.

[29]. Qiaoyu Tan, Yanming Yu, Guoxian Yu, Jun Wang*. Semi-supervised multi-label classification using incomplete label information, Neurocomputing (CCF C), 2017, 260: 192-202.

[30]. Jun Wang, Guangjun Yao, Guoxian Yu*. Semi-supervised classification by discriminative regularization, Applied Soft Computing, 2017, 58: 245-255.

[31]. Xia Cao, Guoxian Yu, Wei Ren, Maozu Guo, Jun Wang*. DualWMDR: detecting epistatic interaction with dual screening and multifactor dimensionality reduction, Human Mutation, 2020, 41(3): 719-734.

[32]. Jie Liu, Guoxian Yu, Yazhou Ren, Maozu Guo, Jun Wang*. TrioMDR: detecting SNP interactions in trio families with model-based multifactor dimensionality reduction, Genomics, 2019, 111(5): 1176-1182.

[33]. Long Zhang, Guoxian Yu, Maozu Guo, Jun Wang*. Predicting protein-protein interactions using high-quality non-interacting pairs, BMC Bioinformatics (CCF C), 2018, 19(S19): 525.

[34]. Xia Cao, Jie Liu, Maozu Guo, Jun Wang*. HiSSI: high-order SNP-SNP interactions detection based on efficient significant pattern and differential evolution, BMC Medical Genomics, 2019, 12(S7): 139.

[35]. Jie Liu, Guoxian Yu, Yuan Jiang, Jun Wang*. HiSeeker: Detecting High-Order SNP Interactions Based on Pairwise SNP Combinations, Genes, 2017, 8(6): 153.

[36]. 陈希,王峻*，余国先，崔立真，郭茂祖. 基于单细胞数据的癌症协同驱动模块识别方法.中国科学-信息科学, 2023, 53(2): 250-265.

[37]. 谭好江，王峻*，余国先，陈建，郭茂祖. 基于个性化随机游走的基因-表型关联分析.电子学报, 2023.

[38]. 王星，王峻*，余国先，郭茂祖.基于网络约束双聚类的癌症亚型分类.计算机学报, 2019, 42(6): 1274-1288.

[39]. 谭桥宇，余国先，王峻*，郭茂祖.基于标记与特征依赖最大化的弱标记集成分类,软件学报, 2017,28(11): 2851-2864.

[40]. 余国先，王可尧，傅广垣，王峻*，曾安.基于多网络数据协同矩阵分解的蛋白质功能预测,计算机研究与发展, 2017,54(12): 2660-2673.

会议论文

[1]. Dezhi Yang, Guoxian Yu, Jun Wang*, Jinglin Zhang, Carlotta Domeniconi. Causal Discovery from Shifted Multiple Environments, ACM SIGKDD international conference on knowledge discovery & data mining (KDD) (CCF A), 2025.

[2]. Dezhi Yang, Xintong He, Jun Wang*, Guoxian Yu, Carlotta Domeniconi, Jinglin Zhang. Federated Causality Learning with Explainable Adaptive Optimization. 38th AAAI Conference on Artificial Intelligence (AAAI) (CCF A) , 2024, pp. 16308-16315

[3]. Zijun Gao, Jun Wang*, Guoxian Yu, Zhongmin Yan, Carlotta Domeniconi, Jinglin Zhang. Long-tail Cross Modal Hashing. 37th AAAI Conference on Artificial Intelligence (AAAI) (CCF A) , 2023.

[4]. Dezhi Yang, Guoxian Yu, Jun Wang*, Zhengtian Wu, Maozu Guo. Reinforcement Causal Structure Learning on Order Graph. 37th AAAI Conference on Artificial Intelligence (AAAI) (CCF A) , 2023.

[5]. Shaowei Wei, Jun Wang*, Guoxian Yu, Carlotta Domeniconi, Xiangliang Zhang. Multi-View Multiple Clusterings using Deep Matrix Factorization, 34rd AAAI Conference on Artificial Intelligence (AAAI) (CCF A), 2020, pp. 6348-6355.

[6]. Xing Wang, Jun Wang*, Carlotta Domeniconi, Guoxian Yu, Guoqiang Xiao, Maozu Guo. Multiple Independent Subspace Clusterings, 33rd AAAI Conference on Artificial Intelligence (AAAI) (CCF A), 2019, pp. 5353-5360.

[7]. Shaowei Wei, Jun Wang*, Guoxian Yu, Carlotta Domeniconi, and Xiangliang Zhang. Deep Incomplete Multi-View Multiple Clusterings, IEEE International Conference on Data Mining (ICDM) (CCF B), 2020, pp. 651-660.

[8]. Xing Wang, Guoxian Yu, Carlotta Domeniconi, Jun Wang*, Zhiwen Yu, and Zili Zhang. Multiple Co-Clusterings, International Conference on Data Mining (ICDM) (CCF B), 2018, pp. 1308-1313.

[9]. Dezhi Yang, Guoxian Yu, Jun Wang*, Zhongmin Yan, Maozu Guo. Causal Discovery by Graph Attention Reinforcement Learning. SIAM International Conference on Data Mining (SDM) (CCF B) , 2023.

[10]. Shixin Yao, Guoxian Yu, Xing Wang, Jun Wang*, Carlotta Domeniconi, Maozu Guo. Discovering Multiple Co-Clusterings in Subspaces, SIAM Conference on Data Mining (SDM) (CCF B), 2019, pp. 423-431.

[11]. Haojiang Tan, Jun Wang*, Guoxian Yu, Wei Guo, and Maozu Guo. Phenotype Prediction by Heterogeneous Molecular Network Embedding. IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (CCF B) , 2022. 

[12]. Xin Wang, Jun Wang*, Guoxian Yu, Beibei Xin, and Maozu Guo. Maize Epistasis Detection by Multi-class Quantitative Multifactor Dimensionality Reduction. IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (CCF B) , 2021, pp. 314-319. 

[13]. Haojiang Tan, Sichao Qiu, Jun Wang*, Guoxian Yu, Wei Guo, and Maozu Guo. Genome-Phenome Association Prediction by Deep Factorizing Heterogeneous Molecular Network. IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (CCF B) , 2021, pp. 211-216. 

[14]. Huiling Zhang, Jun Wang*, Guoxian Yu, Lizhen Cui, Maozu Guo. Epistasis Detection using Heterogeneous Bio-molecular Network, IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (CCF B), 2020, pp. 194-199.

[15]. Sufang Li, Jun Wang*, Maozu Guo, and Xiangliang Zhang. Cooperative Driver Pathway Discovery byHierarchical Clustering and Link Prediction., IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (CCF B), 2020, pp. 194-199.

[16]. Ziying Yang, Guoxian Yu, Jiantao Yu, Maozu Guo, Jun Wang*. CoPath: discovering cooperative driver pathways using greedy mutual exclusivity and bi-clustering, IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (CCF B), 2019, pp. 165-170.

[17].Guoxian Yu, Yuehui Wang, Jun Wang*, Guangyuan Fu, Maozu Guo, and Carlotta Domeniconi. Weighted matrix factorization based data fusion for predicting lncRNA-disease associations, IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (CCF B), 2018, pp. 572-577.

科研项目  

1.国家重点研发计划项目课题，时空***分析技术研究（主持，2024-2027，国拨423万）

2.国家自然科学基金（重点）课题，大规模深度聚类的基础理论、高效算法与应用研究（主持，2025-2029）

3.国家自然科学基金（面上），基于多聚类的单细胞数据分析研究（主持，2023-2026）

4.国家自然科学基金（面上），癌症跨性状协同驱动通路识别研究（主持，2021-2024）

5.国家自然科学基金（面上）, 基于多层次数据整合的复杂疾病遗传关联分析方法研究（主持，2019-2019）

6.国家自然科学基金（青年），基于概率图与自适应聚类的混合特征种群结构推断方法研究（主持，2012-2014）

7.泰山学者青年专家经费（山东省组织部，山东省教育厅），（主持，2023-2025）

8.山东省重大科技创新工程项目，大规模通用人工智能模型开发（子课题负责人，2024-2026）

9.中国人工智能学会-华为MindSpore学术奖励基金(B类),基于MindSpore框架的单细胞组学数据多聚类方法研究(主持，2022-2023)

10.人才引进经费（山东大学），人工智能+生物医学数据挖掘(主持，2020-2025)

11.重庆市基础与前沿研究项目（面上），蛋白质不相关功能标注预测模型研究与应用（主持，2016-2019）

12.中央高校基本科研业务费（重点项目），基于多组学数据融合的复杂疾病遗传关联模式挖掘方法研究（主持，2019-2020）

13.中央高校基本科研业务费（学科团队），生物信息学，（主持，2015-2016）

邮编 : 250101

通讯/办公地址 : 中国济南高新技术产业开发区舜华路1500号，山东大学软件学院

邮箱 : kingjun@sdu.edu.cn

2006.9 -- 2010.7
哈尔滨工业大学       人工智能与信息处理       研究生(博士)毕业       工学博士学位       导师：郭茂祖教授

2004.9 -- 2006.7
哈尔滨工业大学       计算机科学与技术       研究生(硕士)毕业       工学硕士学位       导师：李生教授

2000.9 -- 2004.7
哈尔滨工业大学       计算机科学与技术       本科(学士)       工学学士学位

2013.08 -- 2014.08

罗彻斯特大学      生物统计与计算生物系      访问学者

2010.07 -- 2020.06

西南大学      计算机与信息科学学院      副教授

人工智能、大数据挖掘分析与生物信息学