• 其他栏目

    王峻

    • 教授 博士生导师 硕士生导师
    • 性别:女
    • 毕业院校:哈尔滨工业大学
    • 学历:博士研究生毕业
    • 学位:工学博士学位
    • 在职信息:在职
    • 所在单位:山东大学-南洋理工大学人工智能国际联合研究院
    • 入职时间: 2020-06-12
    • 学科:软件工程其他专业
    • 办公地点:山东大学软件园校区软件学院
    • 联系方式:kingjun@sdu.edu.cn wjkingjun@gmail.com
    • 电子邮箱:kingjun@sdu.edu.cn

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    个人简介

    工学博士,山东大学教授,博/硕士生导师。中国计算机学会高级会员(人工智能与模式识别专委会委员、生物信息学专委会委员),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,机器学习专委会通讯委员),IEEE/ACM会员,中国生物工程学会会员。IJCAI, AAAI, ECML, SDMBIBM等国际国内重要会议程序委员会委员(Senior/Program Committee);Nature Communications, TNNLS,TCYB, TII, TCBB, 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。

    主要从事机器学习(大规模数据特征选择,复杂数据聚类分析,基于深度学习的数据分析);数据挖掘(多源数据整合分析、多维数据网络构建与模式挖掘,大规模数据的并行分析);生物信息学(面向复杂疾病的生物特征识别,遗传交互作用识别,多组学数据遗传关联分析)等领域研究。先后主持(完成)国家自然科学基金3项(62072380, 61873214, 61101234),重庆市自然科学基金1项。获得重庆市科技奖励(科技进步/自然科学)三等奖各1项(2018/2019)。在国内外主流会议和期刊(AAAI, IJCAI, TNNLS, TCYB, Bioinformatics, BiB, TCBB, 计算机学报, 软件学报等)发表论文100余篇。

     研究团智能数据工程与分析实验室(WWW.SDU-IDEA.CN

    招生信息(2023)(*表示名额尚未确定): 

    (1)学术型博士: 软件工程(*),人工智能(*)

    (2)专业型博士: 电子信息(*

    (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)




    期刊论文,完整论文列表


    [1]. 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), 2021, 51(7): 3576-3587.

    [2]. 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), 2021, 22(2): 1984-1999.

    [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), 2020, 63: 153-165.

    [4]. 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), 2020, 36(1): 303-310.

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

    [6]. 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), 2022, 33(9): 4311-4321.

    [7]. 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), 2022, 34(5): 2091-2105.

    [8]. 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, In Print.

    [9]. 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.

    [10]. 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.

    [11]. 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.

    [12]. 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.

    [13]. 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.

    [14]. 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.

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

    [16]. 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.

    [17]. Guoxian Yu*, Guangyuan Fu, Chang Lu, Yazhou Ren, Jun Wang*. BRWLDA: Bi-random walks for predicting lncRNA-disease associations, Oncotarget, 2017, 8(36): 60429-60446.

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

    [19]. 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.

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

    [21]. 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.

    [22]. Ziying Yang, Guoxian Yu, Maozu Guo, Jun Wang*. CoDP: Cooperative driver pathways discovery with matrix factorization and tri-random walk, IEEE Access, 2019, 7(1): 77738-77749.

    [23]. Yanming Yu, Jun Wang*, Qiaoyu Tan, Lianyin Jia, Guoxian Yu. Semi-supervised Multi-label Dimensionality Reduction based on Dependence Maximization, IEEE Access, 2017, 5: 21927-21940.

    [24]. Xia Cao,Guoxian Yu, Jie Liu, Lianyin Jia, Jun Wang*. ClusterMI: Detecting High-Order SNP Interactions based on Clustering and Mutual Information, International Journal of Molecular Sciences, 2018, 19(8), 2267.

    [25]. Jun Wang, Long Zhang, Lianyin Jia, Yazhou Ren, Guoxian Yu*. Protein-Protein Interactions Prediction using a Novel Local Conjoint Triad De of Amino Acids Sequence, International Journal of Molecular Sciences, 2017, 18(11), 2373.

    [26]. Guoxian Yu, Xianxue Yu, Jun Wang*. Network-aided Bi-Clustering for discovering cancer subtypes, Scientific Reports, 2017, 7: 1046.

    [27]. Xianxue Yu, Guoxian Yu, Jun Wang*. Clustering cancer gene expression data by projective clustering ensemble, PLoS ONE, 2017, 12(2): e0171429.

    [28]. Guoxian Yu, Yingwen Zhao, Chang Lu, Jun Wang*. HashGO: Hashing Gene Ontology f protein function prediction, Computational Biology Chemistry, 2017, 71:264-273.

    [29]. Jie Liu, Jun Wang*, Guoxian Yu. Protein Function Prediction by Random Walks on a Hybrid Graph, Current Proteomics, 2016, 13(2): 130-142.

    [30]. 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.

    [31]. 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.

    [32]. 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]. 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.

    [2]. 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.

    [3]. 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.

    [4]. 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.

    [5]. 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.

    [6]. 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.

    [7]. 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.

    [8]. 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.

    [9].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.

    [10]. Huiling Zhang, Guoxian Yu, Wei Ren, Maozu Guo and Jun Wang*. EpIntMC: detecting epistatic interactions using multiple clusterings, 16th International Symposium on Bioinformatics Reseach and Application (ISBRA) (CCF C). 2020, pp. 56-67.


    科研项目  


    1.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)

    2.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)

    3.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)

    4.国家自然科学基金(青年基金),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)

    5.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)

    6.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)

    7.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)

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










    教育经历

    2006.9 -- 2010.7
    哈尔滨工业大学       人工智能与信息处理       工学博士学位

    2004.9 -- 2006.7
    哈尔滨工业大学       计算机科学与技术       工学硕士学位

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

    工作经历

    2013.8 -- 2014.8

    罗彻斯特大学      生物统计与计算生物系      访问学者

    2010.7 -- 2020.6

    西南大学      计算机与信息科学学院      副教授