山东大学软件学院教授，国家级青年人才，国家重点研发项目负责人，山东省杰青，齐鲁青年学者（第一层次），泰山学者青年专家，小米青年学者。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。在国内外主流期刊和会议(TKDE, TDSC, TNNLS, Information Fusion, NAR, Bioinformatics, KDD, ICDE, AAAI, IJCAI, 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（2020）（余国先，郭茂祖，王峻等），山东计算机学会自然科学一等奖（2023）（余国先，王峻，郭茂祖）,全球前2%顶尖科学家（2020-2023）。主持(完成)国家重点研发青年科学家项目和中医药现代化项目子课题各1项，国家自然科学基金4项(62031003，61872300, 61741217, 61402378)，省自然科学基金3项，阿里巴巴全球研究计划项目和山大地纬研发横向项目各1项，泰山学者青年专家科研经费。现担任 中国科学基金，计算机科学，IEEE Transactions on Neural Networks and Learning Systems, Fundamental Research, Neurocomputing, Interdisciplinary Sciences: Computational Life Sciences, Frontier in Genetics, Mathematics和Robotics & Intelligence等期刊编委(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（Area Chair，Senior Program Committee)，和Nature/Science子刊，TPAMI, TKDE, TNNLS, Information Fusion, Genome Biology, Bioinforamtics, 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CCF大数据、人工智能与模式识别、数据库、生物信息学专委会执行委员;中国人工智能学会生物信息学与人工生命、机器学习专委会委员。科技部、国家自科基金、瑞士/新西兰等国科技项目和多个省市科技项目（奖励）的函评（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（*)，人工智能(*)

(2)专业型博士: 电子信息（*）

(3)学术型硕士: 软件工程+人工智能（2）

(4)专业型硕士: 电子信息（3）

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)！

如果您对学术科研感兴趣，培养您发主流期刊和会议论文；如果您对实际工程感兴趣，指导您做可信人工智能和大数据相关的工程项目。

欢迎立志做可信人工智能+大数据分析研究与应用的同学加入团队（博士、硕士和科研助理均有空额，每人会提供一对一的指导+研究生传帮带+团队文体活动(2~3次/周)）

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*, Qingzhong Li, Jun Wang, Hui Li, Carlotta Domeniconi. Incentive-boosted Federated Crowdsourcing. IEEE International Conference on Data Engineering (ICDE) (CCF A) , 2024, pp. 4180-4193.

[2] Cong Su+, Guoxian Yu*, Jun Wang, Hui Li, Qingzhong Li*, Han Yu. Multi-dimensional Fair Federated Learning. 38th AAAI Conference on Artificial Intelligence (AAAI) (CCF A) , 2024, pp. 15083-15090.

[3] Jiaxuan Liang+, Jun Wang, Guoxian Yu*, Shuying Xia, Guoyin Wang. Multi-granularity Causal Structure Learning. 38th AAAI Conference on Artificial Intelligence (AAAI) (CCF A) , 2024, pp. 13727-13735.

[4] 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,  pp. 6021-6029.

[5] 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.

[6]  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.

[7] 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.

[8] 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.

[9] 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.

[10] 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.

[11] 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.

[12] 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.

[13] 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.

[14] 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.

[15] 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.

[16]  Yunfeng Zhao+, Xu Yan, Xiaoqiang Gui+, Shuguang Han*, Guoxian Yu*, Jufeng Chen, Zhao Xu, Bo Zheng. Entire space cascade delayed feedback modeling for effective conversion rate prediction. ACM Conference on Information and Knowledge Management (CIKM) (CCF B) , In Print.

[17]  Xiaoqiang Gui+, Yueyao Cheng, Xiangrong Sheng, Yunfeng Zhao+, Guoxian Yu*, Shuguang Han, Yuning Jiang, Jian Xu and Bo Zheng. Calibration-compatible Listwise Distillation of Privileged Features for CTR Prediction. ACM International Conference Web Search and Data Mining (WSDM) (CCF B) , In Print.

[18] Yunfeng Zhao+, Guoxian Yu*, Lei Liu, Zhongmin Yan, Carlotta Domeniconi, and Lizhen Cui. Few-Shot Partial Multi-Label Learning. IEEE International Conference on Data Mining (ICDM) (CCF B) , 2021, pp. 932-941.

[19] Xiangping Kang+, Guoxian Yu*, Carlotta Domeniconi, Jun Wang, Wei Guo, Yazhou Ren, and Lizhen Cui. Crowdsourcing with Self-paced Workers. IEEE International Conference on Data Mining (ICDM) (CCF B) , 2021, pp. 280-289.

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

[1] Xiangping Kang+, Guoxian Yu*, Lanju Kong, Carlotta Domenicon, Xiangliang Zhang, Qingzhong Li. FedTA: Federated Worthy Task Assignment for Crowd Workers. IEEE Transactions on Dependable and Secure Computing (TDSC) (CCF A) , 2024, 21(4): 4098-4109.

[2] Yunfeng Zhao+, Xintong He, Guoxian Yu*, Jun Wang, Yongqing Zheng, Carlotta Domeniconi. Personalized Federated Few-Shot Node Classification. SCIENCE CHINA Information Sciences (CCF A) , In Print.

[3] 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) , 2023, 35(9): 8852-8864.

[4] 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 (TKDE) (CCF A) , 2023, 35(10): 10845-10856.

[5] 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.

[6] 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.

[7] 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.

[8] 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.  

[9] 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.

[10] 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.

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

[12] 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.

[13] 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.

[14] 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.

[15] Sichao Qiu+, Mengyi Wang, Yuanlin Yang, Guoxian Yu*, Jun Wang, Zhongmin Yan, Carlotta Domeniconi, Maozu Guo. Meta multi-instance multi-label learning by heterogeneous network fusion. Information Fusion (CCF B) , 2023, 94: 272-283.

[16] 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.

[17] Cong Su+, Guoxian Yu*, Yongqing Zheng, Jun Wang, Zhengtian Wu, Xiangliang Zhang, Carlotta Domeniconi. Causality-based fair multiple decision by response functions. ACM Transactions on Knowledge and Data Engineering (TKDD) (CCF B) , 2024, 18(3): 1-61.

[18] 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.

[19] 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.

[20] 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.

[21] 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. 

Guoxian Yu, Liangrui Ren+, Jun Wang*, Carlotta Domeniconi, Xiangliang Zhang. Multiple Clusterings: Recent Advances and Perspectives. Computer Science Review, 2024, 52: 100621.

[22] Haojiang Tan＋, Maozu Guo, Jian Chen, Jun Wang*, Guoxian Yu*. HetFCM: Functional co-module discovery by heterogeneous network co-clustering. Nucleic Acids Research (CCF B) , 2024, 52, e62.

[23] 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.

[24] 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.

[25] 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.

[26] 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.

[27] 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.

[28] 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.

[29] 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.

[30] 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.

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

[32] 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.

[33] 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.

[34] 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.

[35] 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.

[36] 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.

[37] 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.

[39] 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.

[40] 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.

[41] 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.

[42] 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.

[43] 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.

[44] 赵颖闻+, 王峻, 郭茂祖, 张自力, 余国先*. 基于0-1矩阵分解的蛋白质功能预测. 中国科学-信息科学, 2019, 49(9): 1159-1174.

[45] 路畅+，陈霞，王峻，余国先*，余志文. 基于稀疏语义的蛋白质噪声功能标注识别. 中国科学-信息科学, 2018, 48(8): 1035-1050.

[46] 余国先*，傅广垣+，王峻，郭茂祖. 基于降维的蛋白质不相关功能预测. 中国科学-信息科学, 2017, 47(10): 1349-1368.

[47] 傅广垣+，余国先*，王峻，张自力. 基于有向混合图的蛋白质新功能预测. 中国科学-信息科学, 2016, 46(4): 461-475.

[48] 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.

[49] 傅广垣+，余国先*，王峻，郭茂祖. 基于正负样例的蛋白质功能预测. 计算机研究与发展, 2016, 53(8): 1753-1765.

科研项目  

1. 国家重点研发计划青年科学家项目，海量******关键技术与软件（主持，2024-2026）

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

3. 国家自然科学基金（重点）课题，****的智能处理方法与验证（主持，2021-2025）

4. 国家自然科学基金（面上），面向****的数据整合方法研究（主持，2019-2022）

5. 山东省杰出青年基金，***大数据智能处理与分析（主持，2025-2027）

6. 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）

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

8. 山大地纬研发项目，多源数据********计算平台，（主持，2024-2026）

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

10. 齐鲁青年学者经费（山东大学），（主持，2020-2025）

11. 小米青年学者经费（小米基金会），（主持，2023-2024）

12. 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）

13. 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）

14. 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）

15. 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)

16. 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）