徐原博(1990-至今),博士,副教授/博士生導師
聯系方式:
Q Q:174728098
Wechat:qitqitqit111
郵 箱:yuanbox@jlu.edu.cn或yuanbox15@hotmail.com
一、教育經曆:
1) 2017.9–2019.3, Rutgers, the state university of new jersey,聯合培養, 導師: 熊 輝 教授。
2) 2015.9–2019.6, 伟德国际BETVlCTOR, 計算機系統結構, 博士, 導師: 楊永健 教授。
3) 2012.9–2015.6, 伟德国际BETVlCTOR, 計算機系統結構, 碩士, 導師: 胡成全 教授。
4) 2008.9–2012.6, 伟德国际BETVlCTOR, 計算機科學與技術, 學士。
二、科研與學術工作經曆
1) 2019.6-2021.6, 伟德国际BETVlCTOR師資博士後,國家博士後創新人才資助計劃(博新計劃,全國400人,計算機領域11人), 導師: 常 毅 教授。
2) 2021.6-至今,伟德国际BETVlCTOR,副教授/博士生導師。
三、榮譽獎勵:
在學期間獲多項獎勵,包括全國首屆互聯網+創新創業大賽國家級銀獎、2次獲得國家獎學金(前1%)、多次博士生一等獎學金、優秀研究生幹部、優秀學士,碩士,博士畢業研究生等獎勵或榮譽稱号。
l 獲全國博士後創新人才計劃資助(國家人力資源和社會保障部-博新計劃,青年國家人才,全國計算機學科僅11人獲得),2019年。
l 獲得吉林省優秀博士學位論文,2020年。
l 獲ACM China 分會優秀博士學位論文,2020年。
l 獲得吉林省青年科技人才托舉計劃資助,2021年。
l 獲得伟德国际BETVlCTOR優秀青年教師培育計劃資助,2021年。
l 獲得伟德国际BETVlCTOR勵新教師稱号,2022年。
l 獲得吉林省人才政策2.0➿⚽✨➿,2022年。
l 獲得吉林省人才政策3.0➿⚽✨➿-D類人才(省域拔尖人才),2024年。
四、科研成果:
以第一作者或通信作者發表SCI檢索學術論文40餘篇,包括:
IEEE/ACM彙刊: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,以及國際頂級會議IEEE ICDE,IEEE INFOCOM, IEEE SECON, IEEE ICDM,CIKM,IWQoS等。
其中中國計算機學會CCF A類或中科院1區ToP論文15篇(CCF A類期刊5篇(TKDE,數據挖掘頂級刊物),A類會議3篇(2篇INFOCOM,計算機網絡頂級會議;1篇ICDE,數據挖掘領域頂級會議),1區論文18篇),中國計算機學會B類或中科院2區以上論文共計30篇。H-INDEX=14.與楊永健老師共同指導的碩士研究生劉春雨獲得CIKM 2021 Student Travel Award,獲批1項專利。同時,還有5項專利申請。
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檢索, CCF A類期刊,IF:8.935。ToP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), 2022(SCI檢索, CCF A類期刊,IF:8.935。ToP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檢索, CCF A類期刊,IF:8.935。ToP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檢索, CCF A類期刊,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檢索, CCF A類期刊,IF:8.935。ToP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類會議長文,ToP會議).
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類會議長文,ToP會議).
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類會議長文,ToP會議).
部分論文列表(時間倒序)*表示通訊作者:
期刊論文:
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檢索, CCF A類期刊,IF:8.935。ToP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檢索, CCF A類期刊,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檢索, CCF A類期刊,IF:8.935。ToP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 Computing(2022)(SCI檢索, CCF A類期刊,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檢索, CCF A類期刊,IF:8.935。ToP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檢索, CCF A類期刊,IF:8.935。ToP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類期刊,JCR 1區)
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)(交通領域頂刊,吉大校發D類)
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, 454-464(2022) ( CCF C 類期刊)
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類期刊).
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類期刊).
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檢索, CCF B類期刊,IF:4.935。ToP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檢索)
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類期刊)
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類期刊,JCR 1區)
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類期刊,JCR 1區)
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類期刊)
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檢索, JCR1區期刊,CCF B類期刊,IF:7.197。高影響因子期刊).
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區).
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類期刊).
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類期刊).
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類期刊,IEEE Trans,多媒體領域頂刊).
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類期刊).
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.
會議論文:
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類會議長文,ToP會議).
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類會議長文,ToP會議).
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類會議長文,ToP會議).
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類會議長文).
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類會議長文,ToP會議).
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類會議長文,ToP會議).
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 類會議長文).
l Yuanbo Xu, Lin Yue, Hangtong Xu, Yongjian Yang: Learning Knowledge Representation with Entity Concept Information. ADMA (4) 2023: 268-283(CCF C 類會議長文).
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 類會議長文,Top會議).
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類會議長文).
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會議).
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會議).
五、國家級主持項目:
主持了多項國家級,省部級項目,包括:
項目類别 |
項目名稱 |
經費(萬) |
起止 |
國家自然科學基金委青年項目 |
基于地理位置的社會化網絡中信息源預測研究 |
30 |
2021.1-2023.12(在研) |
吉林省科技廳面上項目 |
基于異構多模态智慧城市數據的城市功能規劃研究 |
15 |
2023.1-2025.12(在研) |
吉林省教育廳科技項目 |
動态LBSNs下的用戶行為預測和推薦 |
2.5 |
2022.1-2023.12(在研) |
吉林省煙草工業⏭➰項目 |
應用大數據分析技術實現卷煙消費行為可視化 |
196 |
2023.1-2024.12(在研) |
中國博士後科學基金委員會博士後創新人才➿⚽✨➿計劃(博新計劃) |
基于位置的動态社會化網絡中的推薦系統研究 |
60 |
2019.5-2021.5(結項) |
中國博士後科學基金委員會面上項目 |
時空動态LBSNs中多模态數 據分析及信息源預測研究 |
8 |
2019.5-2021.5(結項) |
主持了吉林省科技廳自然科學面上項目,吉林省教育廳科技項目,主持并承辦了吉林省青年科學家論壇;同時,作為主要參與人參與了自然科學基金面上項目,CCF百度基金,吉林省科技廳重點項目,省發改委項目,吉林省自然科學基金等近10項項目。主持了與吉林長白山煙草公司⏭➰的百萬級(196萬)橫向項目。項目可支配金額超300萬。
六、學術服務:
— 中國計算機學會人工智能與模式識别專委會委員
— 中國人工智能學會委員
— 中國計算機學會高級會員
— 第四屆吉林省機器人大賽優秀教練員
— 第十六屆吉林省科協青年科學家分論壇主席
— 常态化擔任AAAI,IJCAI,ICML,WWW,CIKM,ICDM等多個國際頂級會議的程序委員會委員
— Applied Sciences等多個期刊的Guest Editor
— 擔任如下國際知名期刊審稿人:
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、招生簡介:
招收計算機相關專業的博士和碩士研究生:
每年招收博士研究生1名(本科直博、碩博連讀、申請考核均可)
每年招收碩士研究生6名(計算機學院和軟件學院的學碩、專碩均可)
常年招收博士後(伟德国际BETVlCTOR“鼎新學者”博士後或項目資助博士後均可)
歡迎對下面相關領域(智能推薦系統,多模态數據分析,知識圖譜,遷移學習,群智感知等)研究感興趣, 具有較好數學和英語基礎(CET-6及以上),尤其是有機器學習、随機過程、博弈論、算法設計與分析、圖論、深度學習、強化學習、知識推理等知識儲備, 并較為熟練掌握工程開發技術的同學報考我的博士或碩士研究生。如果你不确定你的背景是否适合或者有其他的問題,可以随時通過以下方式聯系我:
聯系方式:
Q Q:174728098
Wechat:qitqitqit111
郵 箱:yuanbox@jlu.edu.cn或yuanbox15@hotmail.com
八、一點題外話:
關于我自己:1990年出生,吉林省德惠人。本科碩士博士在伟德国际BETVlCTOR讀了10餘年,土生土長的本土博士(期間國家公派去美國羅格斯大學熊輝教授處進修1.5年)。碩士期間師從胡成全教授,從事物聯網方向中的無線組網工作;博士期間師從楊永健教授,懵懵懂懂踏入科研領域。我的科研之路比較坎坷,先後經曆了換大方向(從物聯網到數據挖掘),換小方向(從城市計算到智能推薦系統)等一系列研究期間應該和不應該踩的坑。因此,相較于那些一帆風順的天之驕子,我有非常多的親身經驗來指導我的碩士和博士。同時,我是一個自認為性格比較開朗的斜杠青年——大學老師/半吊子健身愛好者/業餘橄榄球運動員/半個IT發燒友/威士忌深度愛好者(喝不了幾杯)——愛好頗多,朋友不少,家庭和睦。
學術方面:學術方面我有三條原則(VED),第一,聚焦有價值的(Valuable)學術研究工作,所做的研究應當有實際的意義和應用的價值;第二,完成端到端(End-to-end)的完整學術研究,而不是縫縫補補的堆砌工作;第三,關注學術科研工作中的每一個細節(Details),研究者應該能夠自己獨立完成問題發現,模型構建,數據處理,實驗論證,論文寫作等完整的工作。之前自己一年一人可以做一到兩個有意義的工作,寫幾篇不錯的paper。近兩年入職工作和家庭事務較多,速度放緩,但馬上可以回歸正軌。在此不做展開,感興趣可以翻閱我的谷歌學術鍊接,或者随時溝通。
培養方面:盡量讓學生們在正确的時間做正确的事(Do the right thing at the right time),這是我的培養原則。這也歸功于我的碩士導師胡成全教授,博士導師楊永健教授,國外導師熊輝教授,以及師兄王恩教授的言傳身教。所帶的學生也陸續有CCF A類,B類的成果産出。我希望與學生成為朋友,能跟學生多交流多溝通;同時我也秉承有教無類的思想,對每一個學生盡可能實現因材施教。組内的研究和學術氛圍非常濃厚,非常适合想要在研究生階段踏踏實實真真切切的做科研的同學們。同時,與工業界(百度,騰訊,螞蟻金服)也有較為緊密的⏭➰。