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    徐庸辉

    • 教授 博士生导师 硕士生导师
    • 性别:男
    • 毕业院校:南洋理工大学
    • 学历:研究生(博士后)
    • 学位:博士
    • 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: 2021-05-11
    • 办公地点:软件园校区3区604
    • 联系方式:xuyonghui@sdu.edu.cn

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    个人简介

    招收人工智能、软件工程方向研究生。欢迎同学们来信咨询(xuyonghui [at] sdu.edu.cn)。


    2024招生信息:

    人工智能专业学术硕士剩余名额)、专业硕士有剩余名额

    软件工程专业学术硕士(有剩余名额)、专业硕士有剩余名额

    研究方向

    可信AI、具身AI、知识图谱、推荐系统、协同计算及其在医疗健康、电子商务、智慧电力、智慧农业方向的应用。

    教育经历

    2011年9月 - 2017年6月,华南理工大学,计算机科学与工程学院,计算机科学与技术,工学博士

    2007年9月 - 2011年6月,河南大学,数学与统计学院,信息与计算科学,理学学士 

    工作经历

    2021年05月,山东大学,山东大学-南洋理工大学人工智能国际联合研究院,教授

    2018年12月起,中新国际联合研究院,人工智能研发平台,兼职研究员

    2018年05月起,南洋理工大学,阿里巴巴-南洋理工大学新加坡联合研究中心,兼职研究员

    2018年05月起,南洋理工大学,新加坡南洋理工大学及英属哥伦比亚大学百合卓越联合研究中心(LILY中心),研究员

    2018年09月-2018年12月,阿里巴巴集团,ICBU国际战略技术部,访问学者

    2014年07月-2014年11月,百度(中国)有限公司,平台测试部,访问学者

    学术兼职

    《众智科学国际期刊副编辑: International Journal of Crowd Science (IJCS)

    Mathematics》客座编辑

    中国计算机学会协同计算专业委员会(CCF TCCC),执行委员

    中国计算机学会服务计算专业委员会(CCF TCSC),执行委员

    中国计算机学会人工智能与模式识别专业委员会,委员

    济南市软件和信息技术服务业专家库,入库专家

    鲁商教育控股有限公司,特聘专家

    国际学术期刊审稿人:

    IEEE Transactions on Knowledge and Data Engineering (TKDE)

    IEEE Transactions on Neural Networks and Learning Systems (TNNLS)

    IEEE Transactions on Industrial Informatics (TII)

    IEEE Transactions on Services Computing (TSC)

    IEEE Transactions on Cybernetics (Cyber)

    IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)

    IEEE Transactions on Big Data (TBD)

    IEEE Transactions on Cognitive Communications and Networking (TCCN)

    ACM Transactions on Knowledge Discovery from Data (TKDD)

    Knowledge-Based System (KBS)

    Knowledge and Information Systems (KAIS)

    Scientific Data

    Engineering Applications of Artificial Intelligence (EAAI)

    Chinese Journal of Electronics 

    Computers in Biology and Medicine

    Health Information Science and Systems

    国际学术会议兼职:

    The 32st International Joint Conference on Artificial Intelligence (IJCAI-23), PC member

    28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022), 审稿人

    The 31st International Joint Conference on Artificial Intelligence (IJCAI-22), 审稿人

    17th CCF Conference on Computer Supported Cooperative Work and Social Computing (ChineseCSCW 2022),审稿人

    International Conference on Crowd Science and Engineering (ICCSE 2021), 程序委员会联合主席

    International Conference on Crowd Science and Engineering (ICCSE 2019), 程序委员

    IEEE International Conference on Agents (ICA 2019) , 程序委员

    International Conference on Ageless Aging (ICAA 2019) , 程序委员

    IEEE International Conference on Agents (ICA 2019), 领域主席

    发表论文

    2024

    • A Survey on Federated Recommendation Systems [Accepted]

          Zehua Sun, Yonghui Xu (Co-first), Yong Liu, Wei He, Yali Jiang*, Fangzhao Wu, Lizhen Cui.

          IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024.

    • TADA: Temporal-aware Adversarial Domain Adaptation for patient outcomes forecasting [Accepted]

          Chang’an Yi , Haotian Chen , Yonghui Xu∗ , Yan Zhou, Juan Du, Lizhen Cui, Haishu Tan.

          Expert Systems with Applications, 2024.

    2023

    • EAPR: explainable and augmented patient representation learning for disease prediction [PDF]

          Jiancheng Zhang, Yonghui Xu*, Bicui Ye, Yibowen Zhao, Xiaofang Sun, Qi Meng, Yang Zhang, Lizhen Cui.

          Health Information Science and Systems, 2023.

    • FedCIO: Efficient Exact Federated Unlearning with Clustering, Isolation, and One-shot Aggregation [PDF]

          Hongyu Qiu, Yongwei Wang, Yonghui Xu, Lizhen Cui, and Zhiqi Shen.

          IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2023.

    • Estimating package arrival time via heterogeneous hypergraph neural network [PDF]

          Lei Zhang, Xingyu Wu, Yong Liu, Xin Zhou, Yiming Cao, Yonghui Xu*, Lizhen Cui*, Chunyan Miao.

          Expert Systems with Applications, 2023.

    • Multi-Granularity Graph Convolution Network for Major Depressive Disorder Recognition [PDF]

          Xiaofang Sun, Yonghui Xu*, Yibowen Zhao, Xiangwei Zheng, Yongqing Zheng, Lizhen Cui*.

          IEEE Transactions on Neural Systems and Rehabilitation Engineering (TNSRE), 2023.

    • Multi-Component Adversarial Domain Adaptation: A General Framework [PDF]

          Chang'an Yi, Haotian Chen, Yonghui Xu*, Huanhuan Chen, Yong Liu, Haishu Tan, Yuguang Yan, Han Yu.

          IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023.

    • Cross-Domain Disentangled Learning for E-Commerce Live Streaming Recommendation [PDF]

          Yixin Zhang, Yong Liu, Hao Xiong,Yi Liu, Fuqiang Yu, Wei He, Yonghui Xu*, Lizhen Cui*, Chunyan Miao.

          IEEE International Conference on Data Engineering (ICDE), 2023.

    • Delivery Time Prediction Using Large-Scale Graph Structure Learning Based on Quantile Regression [PDF]

          Lei Zhang, Xin Zhou*, Zhiwei Zeng, Yiming Cao, Yonghui Xu, Mingliang Wang, Xingyu Wu, Yong Liu, Lizhen Cui*, Zhiqi Shen.

          IEEE International Conference on Data Engineering (ICDE), 2023.

    • MHCCL: Masked Hierarchical Cluster-wise Contrastive Learning for Multivariate Time Series [PDF][Code]

          Qianwen Meng, Hangwei Qian, Yong Liu, Lizhen Cui, Yonghui Xu*, Zhiqi Shen.

          Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2023.

    • MMTN: Multi-modal Memory Transformer Network for Image-Report Consistent Medical Report Generation [Accepted]

          Yiming Cao, Lizhen Cui*, Lei Zhang, Fuqiang Yu, Zhen Li, Yonghui Xu.

          Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2023.

    • Modeling Long- and Short-term User Preferences via Self-Supervised Learning for Next POI Recommendation [Accepted]

          Shaowei Jiang, Wei He, Lizhen Cui, Yonghui Xu, Lei Liu.

          Transactions on Knowledge Discovery from Data (TKDD), 2023.

    • Multi-View Graph Contrastive Learning for Urban Region Representation [Accepted]

          Yu Zhang, Yonghui Xu, Lizhen Cui, Zhongmin Yan.

          International Joint Conference on Neural Networks (IJCNN), 2023.

    • Event Graph Enhanced Narrative Generation [Accepted]

          Caiyan Li, Lizhen Cui, Yonghui Xu, Ning Liu.

         26th International Conference on Computer Supported Cooperative Work in Design (CSCDW), 2023.

    • Dual Graph Multitask Framework for Imbalanced Delivery Time Estimation  [Accepted]

          Lei Zhang, Mingliang Wang, Xin Zhou, Xingyu Wu, Yiming Cao, Yonghui Xu, Lizhen Cui, Zhiqi Shen

         The 28th International Conference on Database Systems for Advanced Applications (DASFAA), 2023.

    • CMT: Cross-modal Memory Transformer for Medical Image Report Generation [Accepted]

          Yiming Cao, Lizhen Cui, Lei Zhang, Fuqiang Yu, Ziheng Cheng, Zhen Li, Yonghui Xu, Chunyan Miao

         The 28th International Conference on Database Systems for Advanced Applications (DASFAA), 2023.

    • Sample and Feature Enhanced Few-Shot Knowledge Graph Completion [Accepted]

          Kai Zhang, Daokun Zhang, Ning Liu, Yonghua Yang, Yonghui Xu, Zhongmin Yan, Hui Li, Lizhen Cui

         The 28th International Conference on Database Systems for Advanced Applications (DASFAA), 2023.

    • DP-MHAN: A Disease Prediction Method based on Metapath Aggregated Heterogeneous Graph Attention Networks [Accepted]

         Zhe Qu, Lizhen Cui, Yonghui Xu

         The 28th International Conference on Database Systems for Advanced Applications (DASFAA), 2023.

    2022

    • Temporal Hypergraph for Personalized Clinical Pathway Recommendation [PDF]

          Fanglin Zhu, Shunyu Chen, Yonghui Xu*, Fuqiang Yu, and Lizhen Cui*.

          IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2022.

    • Feature-Guided Logical Perception Network for Health Risk Prediction [PDF]

          Fuqiang Yu, Lizhen Cui*, Yiming Cao, Fanglin Zhu, Yonghui Xu*, and Ning Liu.

          IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2022.

    • KdINet: Knowledge-driven Interpretable Network for Medical Imaging Diagnosis [PDF]

          Yiming Cao, Lizhen Cui*, Lei Zhang, Fuqiang Yu, Zhen Li, Yonghui Xu*, and Chunyan Miao.

          IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2022.

    • HealthNet: A Health Progression Network via Heterogeneous Medical Information Fusion [PDF]

          Fuqiang Yu, Lizhen Cui, Yiming Cao, Ning Liu*, Weiming Huang, Yonghui Xu*, Hua Lu*.

          IEEE Transactions on Neural Networks and Learning Systems, 2022.

    • Efficient Asynchronous Multi-Participant Vertical Federated Learning [PDF]

          Haoran Shi, Yonghui Xu*, Yali Jiang, Han Yu, Lizhen Cui*

          IEEE Transactions on Big Data, 2022.

    • Balancing Supply and Demand for Mobile Crowdsourcing Services [PDF]

          Zhaoming Li, Wei He*, Ning Liu, Yonghui Xu, Lizhen Cui.

          20th International Conference on Service Oriented Computing.

    • Clinical Phenotyping Prediction via auxiliary task selection and adaptive shared-space correction

          Xiao Yang, Ning Liu, Jianbo Qiao, Haitao Yuan, Teng Ma, Yonghui Xu, Lizhen Cui.

          CAAI International Conference on Artificial Intelligence 2022.

    • XIVA: An intelligent voice assistant with scalable capabilities for educational metaverse

          Jun Lin, Yonghui Xu, Wei Guo, Lizhen Cui, Chunyan Miao.

          CAAI International Conference on Artificial Intelligence 2022.

    • Towards Heterogeneous Federated Learning [Accepted]

          Yue Huang, Yonghui Xu, Lanju Kong, Qingzhong Li*, Lizhen Cui.

          17th CCF Conference on Computer Supported Cooperative Work and Social Computing (ChineseCSCW 2022).

    • Enhancing Sequential Recommendation with Graph Contrastive Learning [PDF]

            Yixin Zhang, Yong Liu, Yonghui Xu*, Hao Xiong, Chenyi Lei, Wei He, Lizhen Cui*, Chunyan Miao

              The 31st International Joint Conference on Artificial Intelligence (IJCAI-22), 2022.

    • CK-Encoder: Enhanced Language Representation for Sentence Similarity [PDF]

            Tao Jiang, Fengjian Kang, Wei Guo, Wei He, Lei Liu, Xudong Lu, Yonghui Xu*, Lizhen Cui*

              International Journal of Crowd Science (IJCS), 2022.

    • ATPL: Mutually enhanced adversarial training and pseudo labeling for unsupervised domain adaptation [PDF]

            Chang'an Yi, Haotian Chen, Yonghui Xu*, Yong Liu, Lei Jiang, Haishu Tan

            Knowledge-Based SystemKBS, 2022.

    • Similarity-Aware Collaborative Learning for Patient Outcome Predcition [PDF]

            Fuqiang Yu, Lizhen Cui, Yiming Cao, Ning Liu, Weiming Huang, Yonghui Xu

             The 27th International Conference on Database Systems for Advanced Applications (DASFAA), 2022.

    • SAER: Sentiment-opinion Alignment Explainable Recommendation [PDF]

            Xiaoning Zong, Yong Liu, Yonghui Xu*, Yixin Zhang, Zhiqi Shen, Yonghua Yang, Lizhen Cui*

             The 27th International Conference on Database Systems for Advanced Applications (DASFAA), 2022.

    • KdTNet: Medical Image Report Generation via Knowledge-driven Transformer [PDF]

            Yiming Cao, Lizhen Cui*, Fuqiang Yu, Lei Zhang, Zhen Li, Ning Liu, Yonghui Xu*

              The 27th International Conference on Database Systems for Advanced Applications (DASFAA), 2022.

    • MVFLS: Multi-participant Vertical Federated Learning based on Secret Sharing [PDF]

            Haoran Shi, Yali Jiang, Han Yu, Yonghui Xu*, Lizhen Cui*

              FL-AAAI, 2022.

    2021

    • Personalized Clinical Pathways Recommendation via Attention Based Pre-trained Model [PDF]

            Xijie Lin, Yuan Li, Yonghui Xu*, Wei Guo, Wei He*,Honglu Zhang, Lizhen Cui*,Chunyan Miao

            IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2021.

    • Regional Covid-19 epidemic prediction based on multi-modal information fusion [PDF]

            Honglu Zhang, Yonghui Xu*, Lei Liu, Xudong Lu, Xijie Lin, Zhongmin Yan, Lizhen Cui*, Chunyan Miao

            IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2021.

    • Heterogeneous Star Graph Attention Network for Product Attributes Prediction [PDF]

            Xuejiao Zhao, Yong Liu*, Yonghui Xu*, Yonghua Yang, Xusheng Luo, Chunyan Miao

            Advanced Engineering Informatics (AEI), 2021.

    • Credit Default Prediction via Explainable Ensemble Learning [PDF]

            Ronghua Xu, Hefeng Meng, Zhiqiang Lin, Yonghui Xu* and Lizhen Cui*

            Proceedings of the 4th International Conference on Crowd Science and Engineering

    • Music Rhythm Matching Based on Dynamic Step Frequency  [PDF]

            Youyang Du, Chi Zhang, Escoffier Wang, Yunsen Tang, Yonghui Xu* and Lizhen Cui*    

            Proceedings of the 4th International Conference on Crowd Science and Engineering

    • A Serious Mobile Game for Neurodegenerative Diseases Evaluation [PDF]

            Huiguo Zhang*, Yonghui Xu, Jun Lin, Weiming Li and Zhiqi Shen

            Proceedings of the 4th International Conference on Crowd Science and Engineering

    • Task-oriented Dynamic Knowledge Graph Embedding by Incorporating Temporal Smoothness  [PDF]

            Yonghui Xu, Shengjie Sun, Huiguo Zhang, Chang’an Yi, Yuan Miao, Dong Yang, Xiaonan Meng, Yi Hu, Ke Wang, Huaqing Min, Chunyan Miao*, Hengjie Song*

            ACM Transactions on Knowledge Discovery from Data (TKDD), 2021.

    • A Parkinson's Disease Risk Estimation Method Based on Somatosensory Parkour Mobile Game [PDF]

            Huiguo Zhang*, Yonghui Xu, Jun Lin, Weiming Li and Zhiqi Shen,

            IJCAI-AIF, 2021.

    • Major Depressive Disorder Recognition and Cognitive Analysis Based on Multi-layer Brain Functional Connectivity Networks  [PDF]

            Xiaofang Sun, Xiangwei Zheng*, Yonghui Xu*, Lizhen Cui, Bin Hu,

            IJCAI-AIF, 2021, Best application paper.

    • Contextualized Graph Attention Network for Recommendation with Item Knowledge Graph  [PDF]

            Yong Liu, Susen Yang, Yonghui Xu, Chunyan Miao, Min Yu, Juyong Zhang,

            IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021.

    • Adaptive Power Iteration Clustering  [PDF]

            Bo Liu, Yong Liu*, Huiyan Zhang, Yonghui Xu, Can Tang, Lianggui Tang, Huafeng Qin,

            Knowledge-Based SystemKBS,2021.

    • Improved NSGA-II for the minimum constraint removal problem  [PDF]

            Bo Xu, Feng Zhou, Yonghui Xu, Haoran Xu, Kewen Xu

            International Journal of Embedded Systems (IJES). 14(1): 27-35 (2021)

    2020

    • Kernel-Target Alignment based Non-linear Metric Learning  [PDF]

            Yonghui Xu, Chunyan Miao*, Yong Liu, Hengjie Song*, Yi Hu, Huaqing Min,

            Neurocomputing, 2020.

    • Multi-Component Transfer Metric Learning for Handling Unrelated Source Domain Samples  [PDF]

            Chang'an Yi, Yonghui Xu*, Han Yu*, Yuguang Yan, Yang Liu.

            Knowledge-Based SystemKBS, 2020.

    • Domain Adaptation from Public Dataset to Robotic Perception Based on Deep Neural Network  [PDF]

            Chang’an Yi, Haotian Chen, Xiaosheng Hu, Yonghui Xu,

            2020 Chinese Automation Congress (CAC), 2020

    2019

    • Deep Transfer Learning for Abnormality Detection  [PDF]

            Jie Wei Kong, Yonghui Xu*, Han Yu

            ICCSE 2019.

    • Multi-label Metric Transfer Learning Jointly Considering Instance Space and Label Space Distribution Divergence  [PDF]

            Siyu Jiang, Yonghui Xu, Tengyun Wang, Haizhi Yang, Shaojian Qiu, Han Yu, Hengjie Song*.

            IEEE Access, 2019, 7, 10362-10373.

    • A Novel Transfer Metric Learning Approach Based on Multi-Group  [PDF]

            Chang'an Yi, Yonghui Xu*, Bo Xu, Jingtang Zhong, Zhen Zhu, Pengshuai Yin, Huaqing Min.

            2018 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE, 2018: 2184-2189.

    2018

    • Multi-Instance Transfer Metric Learning by Weighted Distribution and Consistent Maximum Likelihood Estimation  [PDF]

            Yonghui Xu*, Siyu Jiang*, Hengjie Song, Qingyao Wu, Michael K. Ng, Huaqing Min, Shaojian Qiu.

            Neurocomputing, 2018.

    • Feature Selection and Transfer Learning for Alzheimer Disease  [PDF]

            Ke Zhou, Wenguang He, Yonghui Xu, Jie Cai.*

            Applied Sciences-Basel, 2018 8(8), 1372.

    2017

    • A Unified Framework for Metric Transfer Learning  [PDF]

            Yonghui Xu, Sinno Jialin Pan, Hui Xiong, Qingyao Wu, Ronghua Luo, Huaqing Min*, Hengjie Song*.

            IEEE Transactions on Knowledge & Data Engineering (TKDE), 2017, PP(29):1158 – 1171.

    • Online Transfer Learning with Multiple Homogeneous or Heterogeneous Sources  [PDF]

            Qingyao Wu, Hanrui Wu, Xiaoming Zhou, Mingkui Tan, Yonghui Xu, Yuguang Yan, Tianyong Hao.

            IEEE Transactions on Knowledge and Data Engineering (TKDE), 2017, PP(29):1494 – 1507.

    • Multi-Instance Metric Transfer Learning for Genome-Wide Protein Function Prediction  [PDF]

            Yonghui Xu, Huaqing Min, Qingyao Wu*, Hengjie Song*.

            Scientific Reports, 2017, 7. (Nature子刊)

    2016

    • Individual Judgments Versus Consensus: Estimating Query-URL Relevance  [PDF]

            Hengjie Song, Yonghui Xu*, Huaqing Min, Qingyao Wu, Wei Wei, Jianshu Weng, Xiaogang Han, Qing Yang, Jialiang Shi, Jiaqian Gu, Chunyan Miao, Toyoaki Nishida.

            ACM Transactions on the Web (TWEB), 2016, 10(1): 3.

    • Multi-instance multi-label distance metric learning for genome-wide protein function prediction  [PDF]

            Yonghui Xu, Huaqing Min, Hengjie Song, Qingyao Wu*.

            Computational biology and chemistry (APBC), 2016, 63: 30-40.

    • Osteoporosis Recognition Based on Similarity Metric with SVM  [PDF]

            Ke Zhou, Jie Cai*, Yonghui Xu, Tianxiu Wu.

            International Journal Bioautomation, 2016, 20(2): 253-264.

    2012

    • Label transfer for joint recognition and segmentation of 3D object  [PDF]

            Yonghui Xu, Ronghua Luo, Huaqing Min.

            Machine Learning and Cybernetics (ICMLC), 2012 International Conference on. IEEE, 2012, 3: 1188-1192.

    • Coupled hidden semi-Markov conditional random fields based context model for semantic map building  [PDF]

            Ronghua Luo, Huaqing Min, Yonghui Xu, Junbo Li.

            Machine Learning and Cybernetics (ICMLC), 2012 International Conference on. IEEE, 2012, 2: 785-791.

    发明专利

    2023年,发明专利,一种连续POI推荐方法及系统,专利号:CN114579893B

    2023年,发明专利,一种移动服务用户轨迹预测方法及系统,专利号:CN114827904B

    2022年,发明专利,一种具备快速适应力的猪只检测和追踪方法及装置,专利号:ZL202210960003.4

    2020年,发明专利, 一种基于九轴传感器的自适应踢腿状态识别方法及其装置,专利号:CN202011106339.1

    2020年,发明专利, 一种游戏化的帕金森症状等级评估方法及装置,专利号:CN202110016956.0

    2020年,发明专利, 一种基于八段锦的智能养老康复游戏系统和游戏方法,专利号:CN202011206876.3

    2020年,  发明专利, 一种肿瘤分割装置和分割方法,专利号:CN202011341340.2

    2020年,  实用新型专利,一种肿瘤分割装置,专利号:CN202022756580.0

    曾获奖励

    2023年,国家教学成果,“三融一化”的拔尖创新软件人才培养模式探索与实践,二等奖

    2023年,第十八届全国大学生智能汽车竞赛,全国总决赛二等奖,优秀指导教师

    2023年,第九届山东省大学生科技创新大赛,一项人工智能辅助超声内镜下实时识别并诊断胰腺神经内分泌肿瘤的系统,银牌指导教师

    2022年,山东省第九届教学成果奖(高等教育类),“三融一化”的拔尖创新软件人才培养模式探索与实践,特等奖

    2022年,山东省第九届教学成果奖(高等教育类),面向世界前沿的“四位一体”螺旋式“人工智能+X”研究生培养模式,二等奖

    2022年,第十七届全国计算机支持的协同工作与社会计算学术会议(ChineseCSC2022),最佳审稿人奖

    2021年,IJCAI'21认知和身体虚弱人工智能国际研讨会,最佳应用论文奖

    2018年,广东省计算机学会优秀论文奖,一等奖

    2015年,广东省计算机学会科学技术奖,ATM智能安防系统,三等奖

    2013年,第15届全国机器人锦标赛,冠军

    2011年,海峡两岸机器人学术研讨会暨机器人技术邀请赛,三等奖

    2011年,广东省机器人大赛,服务机器人组,冠军

    主持项目

    国家自然科学基金(重大项目)子课题:医联网环境下的数据治理与数据跨域分析,2023-2027

    国家自然科学基金(青年科学基金项目):面向大规模多方协同学习的知识迁移关键技术研究,2023-2025

    国家重点研发计划子课题:服务效能理论与技术研究及应用,2022-2024

    山东省优秀青年科学基金项目(海外):大规模跨域知识迁移与协同推理计算,2023-2025

    山东省自然科学基金:面向不完全标记数据的对抗迁移学习研究,2023-2025

    国家电网科技服务项目:基于故障录波数据的架空输电线路故障类型智能诊断技术研究,2023-2025

    山东大学-新腾-商易通联合研究项目:基于多模态数据融合的农作物产量及价格预测系统,2023-2025

    山东大学基本业务科研费资助项目:面向医疗知识图谱的知识融合及补全方法研究,2021-2024

    中新国际联合研究项目:具备快速适应力的智慧农业技术平台,2021-2024

    阿里巴巴创新研究计划:基于动态需求的自适配ETA预测及置信度分析, 2021-2022

    阿里巴巴创新研究计划:电商知识图谱补全及常识性知识挖掘, 2020-2021

    阿里巴巴创新研究计划:基于知识图谱的B2B跨境电商导购场域建设, 2020-2021

    中国博士后科学基金面上项目(一等资助),2018-2021

    博士后国际交流计划派出项目,2018-2020

    参与项目

    山东省科技计划项目:山东省信息技术领域科技发展战略研究,2021-2022

    中新国际联合研究项目:人工智能+ 健康养老技术研究,2018-2020

    阿里巴巴创新研究计划:基于众包的B2B交互式领域知识图谱搭建,2018-2020

    国家自然科学基金:弱监督条件下RGB-D时序图像的语义分割模型与迁移学习算法,2014-2017

    国家自然科学基金:基于行为定向的电子商务平台展示广告精准投放技术研究,2017-2020

    国家自然科学基金:基于多模态深度神经网络的人体行为识别技术研究,2018-2020

    广州市科技计划项目:广州市机器人软件及复杂信息处理重点实验室,2015-2017




    教育经历

    2011.9 -- 2017.6
    华南理工大学       计算机科学与技术       博士研究生毕业       工学博士学位

    2007.9 -- 2011.5
    河南大学       信息与计算科学       本科(学士)       理学学士学位

    工作经历

    2021.5 -- 至今

    山东大学      山东大学-南洋理工大学人工智能国际联合研究院(C-FAIR)      教授

    2018.5 -- 2020.11

    南洋理工大学      新加坡南洋理工大学与加拿大英属哥伦比亚大学百合卓越联合研究中心      研究员

    2018.9 -- 2018.12

    阿里巴巴集团      ICBU国际战略技术部      访问学者      负责跨境电商知识图谱建设工作

    2017.10 -- 2021.4

    华南理工大学      软件学院

    2014.7 -- 2014.11

    百度(中国)有限公司      平台测试部      访问学者      负责众包平台用户行为分析,及用户质量度评估体系搭建