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移动智能计算

徐原博

徐原博1990-至今),博士,副教授/博士生导师


联系方式:

Q    Q:174728098

Wechat:qitqitqit111

邮  箱:yuanbox@jlu.edu.cnyuanbox15@hotmail.com


一、教育经历:

1) 2017.9–2019.3, Rutgers, the state university of new jersey,联合培养, 导师: 熊  辉 教授。

2) 2015.9–2019.6, 澳门永利最老登录入口, 计算机系统结构, 博士, 导师: 杨永健 教授。

3) 2012.9–2015.6, 澳门永利最老登录入口, 计算机系统结构, 硕士, 导师: 胡成全 教授。

4) 2008.9–2012.6, 澳门永利最老登录入口, 计算机科学与技术, 学士。


二、科研与学术工作经历

1) 2019.6-2021.6, 澳门永利最老登录入口计算机学院师资博士后,国家博士后创新人才资助计划(博新计划,全国400人,计算机领域11人), 导师: 常 毅 教授。

2) 2021.6-至今,澳门永利最老登录入口计算机学院,副教授/博士生导师。


三、荣誉奖励:

在学期间获多项奖励,包括全国首届互联网+创新创业大赛国家级银奖、2次获得国家奖学金(前1%)、多次博士生一等奖学金、优秀研究生干部、优秀学士,硕士,博士毕业研究生等奖励或荣誉称号。

l 获全国博士后创新人才计划资助(国家人力资源和社会保障部-新计划青年国家人才,全国计算机学科仅11人获得),2019年。

l 获得吉林省优秀博士学位论文,2020年。

l ACM China 分会优秀博士学位论文,2020年。

l 获得吉林省青年科技人才托举计划资助,2021年。

l 获得澳门永利最老登录入口优秀青年教师培育计划资助,2021年。

l 获得澳门永利最老登录入口励新教师称号,2022年。

l 获得吉林省人才政策2.0支持,2022年。

l 获得吉林省人才政策3.0支持-D类人才(省域拔尖人才),2024年。


四、科研成果:

第一作者通信作者发表SCI检索学术论文40余篇,包括:

IEEE/ACM汇刊:IEEE Transactions on Knowledge and Data Engineering(TKDE)、IEEE Transactions on Multimedia(TMM)ACM Transactions on Knowledge Discovery from Data(TKDD)IEEE Transactions on Neural Networks and Learning Systems(TNNLS),IEEE Transactions on Mobile Computing(TMC),IEEE Transactions on Vehicular Technology(TVT)等,以及国际顶级会议IEEE ICDEIEEE INFOCOM, IEEE SECON, IEEE ICDM,CIKMIWQoS等。

其中中国计算机学会CCF A类或中科院1ToP论文15篇(CCF A类期刊5篇(TKDE,数据挖掘顶级刊物),A类会议3篇(2INFOCOM,计算机网络顶级会议;1ICDE,数据挖掘领域顶级会议),1区论文18篇),中国计算机学会B类或中科院2区以上论文共计30篇。H-INDEX=14.与杨永健老师共同指导的硕士研究生刘春雨获得CIKM 2021 Student Travel Award,获批1项专利。同时,还有5项专利申请。

部分代表作:


l Yuanbo Xu, En Wang∗, Yongjian Yang, Hui Xiong: GS 2 -RS: A Generative Approach for Alleviating Cold start and Filter bubbles in Recommender Systems,IEEE Transactions on Knowledge and Data Engineering:(TKDE), 2023 SCI检索, CCF A类期刊IF8.935ToP期刊).

l Yuanbo Xu, En Wang, Yongjian Yang, Yi Chang: A Unified Collaborative Representation Learning for Neural-Network based Recommender Systems, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022SCI检索, CCF A类期刊IF8.935ToP期刊).

l Yuanbo Xu; Yongjian Yang; En Wang; Fuzhen Zhuang; Hui Xiong: Detect Professional Malicious User with Metric Learning in Recommender Systems, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022 SCI检索, CCF A类期刊IF8.935ToP期刊).

l En Wang, Yuanbo Xu*, Yongjian Yang, Yiheng Jiang, Fukang Yang, Jie Wu: Zone-Enhanced Spatio-Temporal Representation Learning for Urban POI Recommendation,IEEE Transactions on Knowledge and Data Engineering:(TKDE), 2023 (SCI检索, CCF A类期刊,IF:8.935。ToP期刊).

l Yiheng Jiang, Yongjian Yang, Yuanbo Xu*, En Wang: Spatial-Temporal Interval Aware Individual Future Trajectory Prediction,IEEE Transactions on Knowledge and Data Engineering(TKDE), 2023 SCI检索, CCF A类期刊IF8.935ToP期刊).

l En Wang, Yuanbo Xu , Yongjian Yang, Fukang Yang, Chunyu Liu and Yiheng Jiang: ToP: Time-dependent Zone-enhanced Points-of-interest Embedding-based Explainable Recommender system, IEEE International Conference on Computer Communications (INFOCOM) 2021 ( CCF A类会议长文,ToP会议).

l En Wang, Yiheng Jiang, Yuanbo Xu, Liang Wang, Yongjian Yang. Spatial-Temporal Interval Aware Sequential POI Recommendation. IEEE International Conference on Data Engineering (ICDE) 2022 ( CCF A类会议长文,ToP会议).

l En Wang, Mijia Zhang, Yuanbo Xu, Haoyi Xiong, Yongjian Yang: Spatiotemporal Fracture Data Inference in Sparse Urban CrowdSensing, IEEE International Conference on Computer Communications (INFOCOM) 2022 ( CCF A类会议长文,ToP会议).


部分论文列表(时间倒序)*表示通讯作者:


期刊论文:


l Yuanbo Xu, En Wang∗, Yongjian Yang, Hui Xiong: GS 2 -RS: A Generative Approach for Alleviating Cold start and Filter bubbles in Recommender Systems, IEEE Transactions on Knowledge and Data Engineering:(TKDE), 2023 SCI检索, CCF A类期刊IF8.935ToP期刊).

l En Wang, Yuanbo Xu*, Yongjian Yang, Yiheng Jiang, Fukang Yang, Jie Wu: Zone-Enhanced Spatio-Temporal Representation Learning for Urban POI Recommendation, IEEE Transactions on Knowledge and Data Engineering:(TKDE), 2023 (SCI检索, CCF A类期刊,IF:8.935。ToP期刊).

l Yiheng Jiang, Yongjian Yang, Yuanbo Xu*, En Wang: Spatial-Temporal Interval Aware Individual Future Trajectory Prediction, IEEE Transactions on Knowledge and Data Engineering(TKDE), 2023 SCI检索, CCF A类期刊IF8.935ToP期刊).

l Hengzhi Wang, Yongjian Yang, En Wang, Wenbin Liu, Yuanbo Xu, Jie Wu: Truthful User Recruitment for Cooperative Crowdsensing Task: A Combinatorial Multi-Armed Bandit Approach,IEEE Transactions on Mobile Computing2022SCI检索, CCF A类期刊ToP期刊).

l Yuanbo Xu, En Wang, Yongjian Yang, Yi Chang: A unified collaborative representation learning for neural-network based recommendersystems,IEEE Transactions on Knowledge and Data Engineering:(TKDE), 2022 SCI检索, CCF A类期刊IF8.935ToP期刊).

l Yuanbo Xu, Yongjian Yang, En Wang, Fuzhen Zhuang, Hui Xiong: Detect professional malicious user with metric learning in recommender systems,IEEE Transactions on Knowledge and Data Engineering(TKDE), 2022 SCI检索, CCF A类期刊IF8.935ToP期刊).

l Yuanbo Xu, Xiao Cai, En Wang, Wenbin Liu, Yongjian Yang, Funing Yang: Dynamic traffic correlations based spatio-temporal graph convolutional network for urban traffic prediction. Inf. Sci. 621: 580-595 (2023) ( CCF B类期刊,JCR 1

l Qiuyang Huang, Hongfei Jia, Yuanbo Xu*, Yongjian Yang, Gaoxi Xiao: Limi-TFP: Citywide Traffic Flow Prediction With Limited Road Status Information. IEEE Trans. Veh. Technol. 72(3): 2947-2959 (2023)(交通领域顶刊,吉大校发D类

l Xin Liu, Yongjian Yang, Yuanbo Xu, Funing Yang, Qiuyang Huang, Hong Wang: Real-time POI recommendation via modeling long-and short-term user preferences,Neurocomputing 467, 454-4642022 ( CCF C 类期刊

l Qiuyang Huang, Yongjian Yang, Yuanbo Xu, En Wang, Kangning Zhu:Human Origin-Destination Flow Prediction Based on Large Scale Mobile Signal Data,Wireless Communications and Mobile Computing:(INFOCOM) 2021 ( CCF C类期刊.

l Qiuyang Huang, Yongjian Yang, Yuanbo Xu, Funing Yang, Zhilu Yuan, Yongxiong Sun:Citywide road-network traffic monitoring using large-scale mobile signaling data,Neurocomputing 444:136-146(2021)( CCF C类期刊.

l Yongjian Yang, Jufeng Hou, Yuanbo Xu:Super Resolution Deduction: Inferring Fine-Grained Capacity for Urban Signal Station Deployment,IEEE Access 9: 23335-23343(2021)

l Yuanbo Xu, Yongjian Yang, En Wang, Jiayu Han, Fuzhen Zhuang, Zhiwen Yu, Hui Xiong: Neural serendipity recommendation: Exploring the balance between accuracy and novelty with sparse explicit feedback,ACM Transactions on Knowledge Discovery from Data (TKDD) 14-4:1-25(2020) (SCI检索, CCF B类期刊IF4.935ToP期刊)

l Yongjian Yang, Xintao Wang, Yuanbo Xu, Qiuyang Huang: Multiagent reinforcement learning-based taxi predispatching model to balance taxi supply and demand,Journal of Advanced Transportation(2020) SCI检索)

l En Wang, Yongjian Yang, Jie Wu, Kaihao Lou, Wenbin Liu, Yuanbo Xu: Budgeted video replacement policy in mobile crowdsensing,Journal of Parallel and Distributed Computing 136:1-13(2020) ( CCF B类期刊

l Yuanbo Xu, Yongjian Yang, Jiayu Han, En Wang, Jingci Ming, Hui Xiong: Slanderous user detection with modified recurrent neural networks in recommender system,Information Sciences 505:265-281(2019) ( CCF B类期刊,JCR 1

l Jiayu Han, Lei Zheng, He Huang, Yuanbo Xu, S Yu Philip, Wanli Zuo:Deep latent factor model with hierarchical similarity measure for recommender systems,Information Sciences 503:521-532(2019) ( CCF B类期刊,JCR 1

l Jiayu Han, Lei Zheng, Yuanbo Xu, Bangzuo Zhang, Fuzhen Zhuang, S Yu Philip, Wanli Zuo: Adaptive deep modeling of users and items using side information for recommendation,IEEE transactions on neural networks and learning systems,31-3:737-748(2019) ( CCF B类期刊

l Yuanbo Xu, Yongjian Yang, Jiayu Han, En Wang, Fuzhen Zhuang, Jingyuan Yang, Hui Xiong: NeuO: Exploiting the sentimental bias between ratings and reviews with neural networks,Neural Networks,111:77-88(2019)SCI检索, JCR1区期刊CCF B类期刊IF7.197。高影响因子期刊).

l Yuanbo Xu, Yongjian Yang, Jiayu Han, Xiang Li, En Wang: Improving Recommendations by Embedding Multi-Entity Relationships With Latent Dual-Metric Learning, IEEE Access,7:9817-9826,2019 (SCI 2).

l Yongjian Yang, Yuanbo Xu, En Wang, Kaihao Lou, Dongming Luan: Exploring influence maximization in online and offline double-layer propagation scheme, Information Sciences 450:182-199,2018 ( CCF B类期刊.

l Yongjian Yang, Yuanbo Xu, Jiayu Han, En Wang, Weitong Chen, Lin Yue: Efficient traffic congestion estimation using multiple spatio-temporal properties, Neurocomputing, 267:344-353,2017 ( CCF C类期刊.

l Yongjian Yang, Yuanbo Xu, En Wang, Jiayu Han, Zhiwen Yu: Improving existing collaborative filtering recommendations via serendipity-based algorithm, IEEE Transactions on Multimedia, 20-7:1888-1900,2017 ( CCF B类期刊,IEEE Trans多媒体领域顶刊.

l Jiayu Han, Wanli Zuo, Lu Liu, Yuanbo Xu, Tao Peng: Building text classifiers using positive, unlabeled and ‘outdated’examples, Concurrency and Computation: Practice and Experience,28-13:3691-3706,2016 ( CCF C类期刊.

l Yuanbo Xu, Lihong Zhong, Lili He: Analysis on node localization method using maximum likelihood estimation based on wireless sensor network [J], Transducer and Microsystem Technologies,30-10:37-43 , 2011.


会议论文:


l En Wang, Yiheng Jiang, Yuanbo Xu, Liang Wang, Yongjian Yang. Spatial-Temporal Interval Aware Sequential POI Recommendation. IEEE International Conference on Data Engineering (ICDE) 2022 ( CCF A类会议长文,ToP会议).

l En Wang, Mijia Zhang, Yuanbo Xu, Haoyi Xiong, Yongjian Yang: Spatiotemporal Fracture Data Inference in Sparse Urban CrowdSensing, IEEE International Conference on Computer Communications (INFOCOM) 2022 ( CCF A类会议长文,ToP会议).

l Chunyu Liu, Yongjian Yang, Zijun Yao, Yuanbo Xu, Weitong Chen, Lin Yue, Haomeng Wu: Discovering Urban Functions of High-Definition Zoning with Continuous Human Traces,Proceedings of the 30th ACM International Conference on Information & Knowledge Management:1048-1057(2021) ( CCF B类会议长文ToP会议).

l En Wang, Pengmin Dong, Yuanbo Xu, Dawei Li, Liang Wang, Yongjian Yang:Distributed Game-Theoretical Task Offloading for Mobile Edge Computing,IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems (MASS):216-224(2021) ( CCF C类会议长文).

l En Wang, Mijia Zhang, Yongjian Yang, Yuanbo Xu, Jie Wu:Exploiting Outlier Value Effects in Sparse Urban CrowdSensing,IEEE/ACM 29th International Symposium on Quality of Service (IWQOS):1-10 2021 ( CCF B类会议长文,ToP会议).

l En Wang, Yuanbo Xu, Yongjian Yang, Fukang Yang, Chunyu Liu, Yiheng Jiang:ToP: Time-dependent Zone-enhanced Points-of-interest Embedding-based Explainable Recommender system,IEEE INFOCOM 2021-IEEE Conference on Computer Communications(INFOCOM) 2021 ( CCF A类会议长文,ToP会议).

l Yuanbo Xu, Yuanbo Zhang, Yongjian Yang, Hangtong Xu, Lin Yue: Duet Representation Learning with Entity Multi-attribute Information in Knowledge Graphs. ADMA (2) 2023: 32-45(CCF C 类会议长文).

l Yuanbo Xu, Lin Yue, Hangtong Xu, Yongjian Yang: Learning Knowledge Representation with Entity Concept Information. ADMA (4) 2023: 268-283(CCF C 类会议长文).

l Jialei Chen, Yuanbo Xu*, Pengyang Wang, Yongjian Yang: Deep Generative Imputation Model for Missing Not At Random Data. CIKM 2023: 316-325(CCF B 类会议长文,Top会议.

l Yuanbo Xu, Yongjian Yang, Jiayu Han, En Wang, Fuzhen Zhuang, Hui Xiong: Exploiting the sentimental bias between ratings and reviews for enhancing recommendation,2018 ieee international conference on data mining (icdm),1356-1361(2018) ( CCF B类会议长文).

l Yu Jiang, Jin Wang, Lili He, Yuanbo Xu, Hongtao Bai: A Low Power Balanced Security Control Protocol of WSN, International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness :46-51 ,2016(EI会议).

l Yuanbo Xu, Yu Jiang, Chengquan Hu, Hui Chen, Lili He, Yinghui Cao: A balanced security protocol of wireless sensor network for smart home, International Conference on Signal Processing (ICSP): 2324-2327, 2014 ( EI会议.


五、国家级主持项目:

主持了多项国家级,省部级项目,包括:



项目类别

项目名称

经费(万)

起止

国家自然科学基金委青年项目

基于地理位置的社会化网络中信息源预测研究

30

2021.1-2023.12(在研)

吉林省科技厅面上项目

基于异构多模态智慧城市数据的城市功能规划研究

15

2023.1-2025.12(在研)

吉林省教育厅科技项目

动态LBSNs下的用户行为预测和推荐

2.5

2022.1-2023.12(在研)

吉林省烟草工业合作项目

应用大数据分析技术实现卷烟消费行为可视化

196

2023.1-2024.12(在研)

中国博士后科学基金委员会博士后创新人才支持计划(博新计划)

基于位置的动态社会化网络中的推荐系统研究

60

2019.5-2021.5(结项)

中国博士后科学基金委员会面上项目

时空动态LBSNs中多模态数 据分析及信息源预测研究

8

2019.5-2021.5(结项)



主持了吉林省科技厅自然科学面上项目,吉林省教育厅科技项目,主持并承办了吉林省青年科学家论坛;同时,作为主要参与人参与了自然科学基金面上项目,CCF百度基金,吉林省科技厅重点项目,省发改委项目,吉林省自然科学基金等近10项项目。主持了与吉林长白山烟草公司合作的百万级(196万)横向项目。项目可支配金额超300万。



六、学术服务:


— 中国计算机学会人工智能与模式识别专委会委员

— 中国人工智能学会委员

— 中国计算机学会高级会员

— 第四届吉林省机器人大赛优秀教练员

— 第十六届吉林省科协青年科学家分论坛主席

— 常态化担任AAAI,IJCAI,ICML,WWW,CIKM,ICDM等多个国际顶级会议的程序委员会委员

Applied Sciences等多个期刊的Guest Editor      

— 担任如下国际知名期刊审稿人:

IEEE Transactions on Pattern Analysis and Machine Intelligence

IEEE Transactions on Knowledge and Data Engineering

IEEE Transactions on Mobile Computing

IEEE/ACM Transactions on Networking

ACM Transactions on Information System

IEEE Transactions on Vehicular Technology

IEEE Transactions on Intelligent Transportation System

IEEE Internet of Things Journal

IEEE Transactions on Communications

IEEE Transactions on Neural Networks and Learning Systems

ACM Transactions on Knowledge Discovery from Data



七、招生简介:

招收计算机相关专业的博士硕士研究生:

  • 每年招收博士研究生1名(本科直博、硕博连读、申请考核均可)

  • 每年招收硕士研究生6名(计算机学院和软件学院的学硕、专硕均可)

  • 常年招收博士后(澳门永利最老登录入口“鼎新学者”博士后或项目资助博士后均可)


欢迎对下面相关领域(智能推荐系统,多模态数据分析,知识图谱,迁移学习,群智感知等)研究感兴趣, 具有较好数学和英语基础(CET-6及以上),尤其是有机器学习、随机过程、博弈论、算法设计与分析、图论、深度学习、强化学习、知识推理等知识储备, 并较为熟练掌握工程开发技术的同学报考我的博士或硕士研究生。如果你不确定你的背景是否适合或者有其他的问题,可以随时通过以下方式联系我:


联系方式:

Q      Q:174728098

Wechat:qitqitqit111

邮  箱:yuanbox@jlu.edu.cn或yuanbox15@hotmail.com


八、一点题外话:


关于我自己:1990年出生,吉林省德惠人。本科硕士博士在澳门永利最老登录入口读了10余年,土生土长的本土博士(期间国家公派去美国罗格斯大学熊辉教授处进修1.5年)。硕士期间师从胡成全教授,从事物联网方向中的无线组网工作;博士期间师从杨永健教授,懵懵懂懂踏入科研领域。我的科研之路比较坎坷,先后经历了换大方向(从物联网到数据挖掘),换小方向(从城市计算到智能推荐系统)等一系列研究期间应该和不应该踩的坑。因此,相较于那些一帆风顺的天之骄子,我有非常多的亲身经验来指导我的硕士和博士。同时,我是一个自认为性格比较开朗的斜杠青年——大学老师/半吊子健身爱好者/业余橄榄球运动员/半个IT发烧友/威士忌深度爱好者(喝不了几杯)——爱好颇多,朋友不少,家庭和睦。


学术方面:学术方面我有三条原则(VED),第一,聚焦有价值的(Valuable学术研究工作,所做的研究应当有实际的意义和应用的价值;第二,完成端到端(End-to-end的完整学术研究,而不是缝缝补补的堆砌工作;第三,关注学术科研工作中的每一个细节(Details),研究者应该能够自己独立完成问题发现,模型构建,数据处理,实验论证,论文写作等完整的工作。之前自己一年一人可以做一到两个有意义的工作,写几篇不错的paper。近两年入职工作和家庭事务较多,速度放缓,但马上可以回归正轨。在此不做展开,感兴趣可以翻阅我的谷歌学术链接,或者随时沟通。


培养方面:尽量让学生们在正确的时间做正确的事(Do the right thing at the right time),这是我的培养原则。这也归功于我的硕士导师胡成全教授,博士导师杨永健教授,国外导师熊辉教授,以及师兄王恩教授的言传身教。所带的学生也陆续有CCF A类,B类的成果产出。我希望与学生成为朋友,能跟学生多交流多沟通;同时我也秉承有教无类的思想,对每一个学生尽可能实现因材施教。组内的研究和学术氛围非常浓厚,非常适合想要在研究生阶段踏踏实实真真切切的做科研的同学们。同时,与工业界(百度,腾讯,蚂蚁金服)也有较为紧密的合作。














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