山东大学软件学院教授，博士生导师，齐鲁青年学者，山东省泰山学者青年专家，国家自然科学基金委流动业务主管（2022-2024）。主要从事人工智能，机器学习，数据挖掘及其在生物医学数据分析中的应用研究。在国内外主流会议和期刊(KDD, AAAI, IJCAI, TKDE, TNNLS, TCYB, Bioinformatics, BiB, TCBB, 中国科学-信息科学, 计算机学报等)发表论文100余篇,获得重庆市科技奖励（自然科学）三等奖（2019）（余国先，郭茂祖，王峻等）。主持(完成)国家自然科学基金3项(61872300, 61741217, 61402378)，联合主持国家自然科学基金重点1项（62031003），国家重点研发子课题，重庆市自然科学基金2项(cstc2018jcyjAX0228, cstc2014jcyjA40031)。现担任Frontier in Genetics，Interdisciplinary Sciences: Computational Life Sciences和Robotics & Intelligence期刊编委(Associate Editor),受邀常年担任KDD, NeurIPS,ICML, IJCAI, AAAI, ICDM, SDM, WSDM, ECAI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, Area Chair)，和Nature/Science系列子刊，TPAMI, TNNLS, TKDE, TCBB, Information Fusion Genome Biology, Bioinforamtics, BiB, 自动化学报，计算机学报，中国科学-信息科学等多个国内外著名期刊审稿人。现任中国计算机学会人工智能与模式识别专委会委员，生物信息学专委会委员，大数据专委会通讯委员;中国人工智能学会生物信息学与人工生命专委会委员，机器学习专委会委员。国家自然科学基金,瑞士联邦基金和多个省部科技计划项目的评审人。曾任西南大学计算机与信息科学学院教授(2018.06-2020.06)，副教授(2013.07-2018.06)。

研究团队：智能数据工程与分析实验室（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（已招满)，人工智能(*)

(2)专业型博士: 电子信息（0）

(3)学术型硕士: 软件工程（已招满），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)！

主要会议论文（+指导的学生，*通讯作者）完整论文列表

[1]. Xiangping Kang+, Guoxian Yu*, Jun Wang, Wei Guo, Carlotta Domeniconi, Jinglin Zhang. Incentive-boosted Federated Crowdsourcing. 37th AAAI Conference on Artificial Intelligence (AAAI) (CCF A) , 2023.

[2]. Yunfeng Zhao+, Guoxian Yu*, Lei Liu, Zhongmin Yan, Lizhen Cui, Carlotta Domeniconi. Few-Shot Partial-Label Learning, International Joint Conference on Artificial Intelligence (IJCAI) (CCF A), 2021, pp. 3448-3454.

[3].  Guangyang Han+, Jinzheng Tu+, Guoxian Yu*, Jun Wang, Carlotta Domeniconi. Crowdsourcing with Multiple-Source Knowledge Transfer, 29th International Joint Conference on Artificial Intelligence (IJCAI) (CCF A), 2020, pp. 2908-2914.

[4]. Yuying Xing+, Guoxian Yu*, Jun Wang, Carlotta Domeniconi, Xiangliang Zhang. Weakly-Supervised Multi-view Multi-instance Multi-label Learning, 29th International Joint Conference on Artificial Intelligence (IJCAI) (CCF A), 2020, pp. 2908-2914.

[5]. Shixin Yao+, Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Xiangliang Zhang. Multi-View Multiple Clustering, 28th International Joint Conference on Artificial Intelligence (IJCAI) (CCF A), 2019, pp. 4121-4127.

[6]. Xia Chen+, Guoxian Yu*, Jun Wang, Carlotta Domeniconi, Zhao Li, Xiangliang Zhang. ActiveHNE: Active Heterogeneous Network Embedding, 28th International Joint Conference on Artificial Intelligence (IJCAI) (CCF A), 2019, pp. 2123-2129.

[7]. Yuying Xing+, Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Zili Zhang, Maozu Guo Multi-View Multi-Instance Multi-Label Learning based on Collaborative Matrix Factorization, 33rd AAAI Conference on Artificial Intelligence (AAAI) (CCF A), 2019, pp. 5508-5515.

[8]. Xuanwu Liu+, Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Yazhou Ren, Maozu Guo. Ranking-based Deep Cross-modal Hashing, 33rd AAAI Conference on Artificial Intelligence (AAAI) (CCF A), 2019, pp. 4400-4407.

[9]. Yuying Xing+, Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Zili Zhang. Multi-Label Co-Training, 27th International Joint Conference on Artificial Intelligence (IJCAI) (CCF A), 2018, pp.2882-2888.

[10]. Qiaoyu Tan+, Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Zili Zhang. Incomplete Multi-View Weak-Label Learning, 27th International Joint Conference on Artificial Intelligence (IJCAI) (CCF A), 2018, pp.2703-2709.

[11]. Guoxian Yu, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zili Zhang. Protein Function Prediction by Integrating Multiple Kernels, Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI) (CCF A), 2013, pp. 1869-1875.

[12]. Guoxian Yu, Carlotta Domeniconi, Huzefa Rangwala, Guoji Zhang, Zhiwen Yu. Transductive Multi-label Ensemble Classification for Protein Function Prediction, Proceedings of the 18th ACM SIGKDD Conference on Knowledge Discovery and Data Mining) (KDD) (CCF A), 2012, pp. 1077-1085.

主要期刊论文（+指导的学生，*通讯作者）. 个人Google Scholar

[1].  Liangrui Ren+, Guoxian Yu*, Jun Wang, Lei Liu, Carlotta Domeniconi, Xiangliang Zhang. A Diversified Attention Model for Interpretable Multiple Clusterings, IEEE Transactions on Knowledge and Data Engineering (TKDE) (CCF A) , In Print.

[2]. 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.

[3]. Xianxue Yu+, Guoxian Yu*, Jun Wang, Carlotta Domeniconi. Co-clustering Ensembles based on Multiple Relevance Measures, IEEE Transactions on Knowledge and Data Engineering (CCF A), 2021, 33(4): 1389-1400.

[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) , In Print.

[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), 2021, 32(4): 1448-1459.

[7]. 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), 2022. 33(9): 4311-4321.

[8]. 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.

[9]. Qiaoyu Tan+, Guoxian Yu*, Jun Wang, Carlotta Domeniconi, Xiangliang Zhang. Individuality and Commonality based Multi-View Multi-Label Learning, IEEE Transactions on Cybernetics (CCF B), 2021, 51(3): 1716-1727.

[10]. Xuanwu Liu+, Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Guoqiang Xiao, Maozu Guo. Weakly-supervised Cross-modal Hashing, IEEE Transactions on Big Data (CCF C), 2021.

[11]. Jinzheng Tu+, Guoxian Yu*, Jun Wang, Carlotta Domeniconi, Maozu Guo, Xiangliang Zhang. CrowdWT: Crowdsourcing via Joint Modeling of Workers and Tasks, ACM Transactions on Knowledge Discovery from Data (CCF B), 2021, 15(1): 12.

[12]. Shaowei Wei+, Guoxian Yu*, Jun Wang, Carlotta Domeniconi, Xiangliang Zhang. Multiple Clusterings of Heterogeneous Information Networks, Machine Learning (CCF B), 2021, 110(6): 1505-1526.

[13]. Guangjin Ou+, Guoxian Yu*, Carlotta Domeniconi, Xuequan Lu, Xiangliang Zhang. Multi-label Zero-Shot Learning with Graph Convolutional Networks, Neural Networks (CCF B), 2020, 137: 333-341.

[14]. Runmin Wang+, Guoxian Yu*, Hong Zhang, Lizhen Cui, Maozu Guo, Xiangliang Zhang. Noise-robust Deep Cross-Modal Hashing. Information Sciences (CCF B) , 2021, 581: 136-154. 

[15]. 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.

[16]. 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.

[17] Sichao Qiu+, Guoxian Yu*, Xudong Lu, Carlotta Domeniconi, and Maozu Guo. Isoform function prediction by Gene Ontology embedding, Bioinformatics (CCF B) , 2022, 33(9): 4311-4321.

[18] 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) , 2022, 38(22):5092-5099.

[19]. Guoxian Yu*, Guangjie Zhou+, Carlotta Domeniconi, Xiangliang Zhang, Maozu Guo*. DMIL-IsoFun: predicting isoform function using deep multi-instance learning, Bioinformatics (CCF B),  2021, 37(24): 4818-4825.

[20]. Keyao Wang+, Jun Wang, Carlotta Domeniconi, Xiangliang Zhang*, Guoxian Yu*. Differentiating isoform functions with collaborative matrix factorization, Bioinformatics (CCF B), 2020, 36(6): 1864–1871.

[21]. 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.

[22]. Guoxian Yu*, Yuan Jiang, Jun Wang, Hao Zhang, Haiwei Luo*. BMC3C: Binning Metagenomic Contigs using Codon usage, sequence Composition and read Coverage, Bioinformatics (CCF B), 2018, 34(24): 4171-4179.

[23]. Guangyuan Fu+, Jun Wang, Carlotta Domeniconi, Guoxian Yu*. Matrix factorization based data fusion for the prediction of lncRNA-disease associations, Bioinformatics (CCF B), 2018, 34(9): 1529-1537.

[24]. Guangyuan Fu+, Jun Wang, Bo Yang, Guoxian Yu*. NegGOA: Negative GO Annotations Selection using Ontology Structure, Bioinformatics (CCF B), 2016, 32(19): 2996-3004.

[25]. Xingze Wang+, Guoxian Yu*, Zhongmin Yan, Lin Wan, Wei Wang, Lizhen Cui. Lung Cancer Subtype Diagnosis by Fusing Image-genomics Data and Hybrid Deep Networks, IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF B), 2023.

[26]. 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.

[27]. 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.

[28]. 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.

[29]. Yingwen Zhao+, Jun Wang, Maozu Guo, Xiangliang Zhang, Guoxian Yu*. Cross-Species Protein Function Prediction with Asynchronous-Random Walk, IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF B), 2021, 18(4): 1439-1450.

[30]. 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.

[31]. Guoxian Yu*, Guangyuan Fu+, Jun Wang, Yingwen Zhao. NewGOA: predicting new GO annotations of proteins by bi-random walks on a hybrid graph, IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF B), 2018, 15(4): 1390-1402.

[32]. Guoxian Yu*, Guangyuan Fu+, Jun Wang, Hailong Zhu. Predicting Protein Function via Semantic Integration of Multiple Networks, IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF B), 2016, 13(2): 220-232.

[33]. Guoxian Yu*, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zili Zhang. Predicting Protein Function using Multiple Kernels, IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF B), 2015, 12(1): 219-233.

[34]. Guoxian Yu*, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zhiwen Yu. Protein Function Prediction with Incomplete Annotations, IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF B), 2014, 11(3): 579-591.

[35]. Guoxian Yu*, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zhiwen Yu. Protein Function Prediction using Multi-label Ensemble Classification, IEEE/ACM Transactions on Computational Biology and Bioinformatics (CCF B), 2013, 10(4): 1045-1057.

科研项目  

1. 国家自然科学基金（重点），玉米基因型-表型数据关联的智能处理方法与验证（合作单位主持，2021-2025）

2. 国家自然科学基金（面上），面向可变剪接异构体功能预测的数据整合方法研究（主持，2019-2022）

3. 国家重点研发计划子课题，基于大规模*****的安全风险信息识别关键技术构建（主持，2023-2025）

4. 阿里巴巴AIR项目，大规模***********，（主持，2022-2023）

5. 山东省重大科技创新工程项目，早期胃癌AI图像识别及检测系统研发（子课题负责人，2021-2024）

6. 齐鲁青年学者经费（山东大学），（主持，2020-2025）

7. 国家自然科学基金（应急管理），基于多层次数据集成的跨物种蛋白质功能预测研究（主持，2018-2018）

8. 国家自然科学基金（青年基金），面向蛋白质功能预测的多标记学习方法研究与应用（主持，2015-2017）

9. 重庆市基础与前沿研究项目（面上），面向跨物种蛋白质功能预测的多源异构数据表示与集成模型研究（主持，2018-2020）

10. 重庆市基础与前沿研究项目（面上），多标记学习方法在蛋白质功能预测中的研究与应用(主持，2014-2017)

11. 人力资源与社会保障部（留学人员科技活动项目择优资助），高维数据上的半监督学习研究与应用（主持，2014-2016）