王柱科研成果

综合介绍 General Introduction 工学博士，西北工业大学计算机学院教授/博导，陕西省青年科技新星。主要从事智能感知、普适计算、人机交互等方面研究工作。在国内外重要期刊和会议如IEEE TMC、IEEE TKDE、ACM UbiComp等高水平期刊/会议上发表论文100余篇，Google学术被引4000余次，4篇论文入选ESI高被引论文；曾获教育部高等学校科技进步一等奖/自然科学二等奖、陕西省科学技术一等奖、陕西高等学校科学技术特等奖，以及IEEE BIBM、IEEE UIC等国际知名学术会议最佳论文奖。担任国际期刊Personal and Ubiquitous Computing、World Wide Web Journal等编委或客座编委，担任领域重要国际会议ACM UbiComp、IEEE INFOCOM等程序委员或审稿人。 个人相册 内容来自集群智慧云企服 实用新型专利1875代写全部资料全国受理

教育教学

教育教学 Education and teaching 招生信息 教育信息 招收计算机科学与技术学科博士研究生（每年1~2名）和硕士研究生（每年2~3名）研究方向：物联网、智能感知、普适计算等欢迎咨询（wangzhu@nwpu.edu.cn）！ 本科生课程：智能感知技术、物联网数据处理硕士生课程：智能无线感知博士生课程：健康感知与计算

荣誉获奖

获奖信息 The winning information 移动网络环境用户行为感知与理解，2020年度陕西省科学技术一等奖（排名3）面向城市精细化治理的数据协同处理关键技术及应用，2020年度教育部科技进步一等奖（排名4） 内容来自集群智慧云企服 实用新型专利1875代写全部资料全国受理

科学研究

科学研究 Scientific Research 国家自然科学基金面上项目，“基于Wi-Fi CSI的多人行为鲁棒感知模型与方法研究”，2021.1-2024.12，负责国家自然科学基金国际合作重点项目，“跨空间用户行为数据处理关键问题研究”，2020.1-2024.12，参与创新TQ课题，“XXX特征深化分析”，2019.10-2023.6，负责创新TQ课题，“XXX特征提取与融合”，2018.9-2021.6，负责国家重点研发计划子课题，“基于多模传感的健康监测与评估技术研究”，2016.7-2020.6，负责国家自然科学基金青年项目，“多模态异构移动社会网络社区发现研究”，2015.1-2017.12 ，负责陕西省青年科技新星项目，“面向人体健康状态评估的多维健康语义识别方法研究 ”，2018.1-2019.12，负责陕西省自然科学基础研究计划青年项目，“面向移动社会网络的重叠式社区发现方法研究”，2015.1-2016.12，负责西北工业大学基础研究基金，“基于持续计算的老年人健康评估模型与促进方法研究”，2014.5-2016.4，负责国家重点基础研究发展计划（973课题），“面向城市大数据的三元空间协同感知方法”，2015.1-2019.12，参与国家自然科学基金重点项目，“面向老年人健康的非干预式感知与持续计算研究”，2014.1-2018.12，参与欧盟第七框架计划项目（EU FP7），“SOCIETIES-基于自组织网络的智能社区交互空间研究”，2010.10-2012.4，参与国家高技术研究发展计划重点项目（863计划），“普适计算软硬件关键技术”，2009.1-2010.10，参与

学术成果

学术成果 Academic Achievements 1. 部分学术论文（期刊）【详见Google Scholar个人页面】[1] X Li, Z Wang, X Chen, B Guo, Z Yu. A Hybrid Continuous-Time Dynamic Graph Representation Learning Model by Exploring both Temporal and Repetitive Information. ACM Transactions on Knowledge Discovery from Data, 2023.[2] Z Wang, ZL Wang, X Li, Z Yu, B Guo, L Chen, X Zhou. Exploring Multi-dimension User-Item Interactions with Attentional Knowledge Graph Neural Networks for Recommendation. IEEE Transactions on Big Data, 2023.[3] Z Yu, D Zhang, Z Wang, Q Han, B Guo, Q Wang. SoDar: Multi-target Gesture Recognition based on SIMO Doppler Radar. IEEE Transactions on Human-Machine Systems, 2022.[4] F Liu, X Zhou, J Cao, Z Wang, T Wang, H Wang, and Y Zhang. Anomaly Detection in Quasi-Periodic Time Series based on Automatic Data Segmentation and Attentional LSTM-CNN. IEEE Transactions on Knowledge and Data Engineering, 2022.[5] P Wang, B Guo, Z Wang, and Z Yu. ShopSense: Customer Localization in Multi-person Scenario with Passive RFID Tags. IEEE Transactions on Mobile Computing, 2022.[6] J Xie, Z Wang, Z Yu, B Guo. Enabling Timely Medical Intervention by Exploring Health-Related Multivariate Time Series with a Hybrid Attentive Model. Sensors 22 (16), 6104: 1-18, 2022.[7] Z Zhang, Z Wang, X Li, N Liu, B Guo, Z Yu. ModalNet: an aspect-level sentiment classification model by exploring multimodal data with fusion discriminant attentional network. World Wide Web 24 (6), 1957-1974, 2021.[8] Z Wang, Z Yu, X Lou, B Guo, and L Chen. Gesture-Radar: a Dual Doppler Radar Based System for Robust Recognition and Quantitative Profiling of Human Gestures. IEEE Transactions on Human-Machine Systems, 2020.[9] Z Wang, ZW Yu, B Zhao, B Guo, C Chen, and ZY Yu. EmotionSense: An Adaptive Emotion Recognition System Based on Wearable Smart Devices. ACM Transactions on Computing for Healthcare, 2020.[10] Z Wang, X Lou, Z Yu, B Guo, and X Zhou. Enabling non-invasive and real-time human-machine interactions based on wireless sensing and fog computing. Personal and Ubiquitous Computing 23 (1), 29-41, 2019.[11] Z Wang, B Guo, Z Yu, and X Zhou. Wi-Fi CSI based Behavior Recognition: from Signals, Actions to Activities. IEEE Communications Magazine, 2018. [12] H Du, Z Yu, F Yi, Z Wang, Q Han, and B Guo. Recognition of Group Mobility Level and Group Structure with Mobile Devices. IEEE Transactions on Mobile Computing, 17(4), 884-897, 2018.[13] Y Jing, B Guo, Z Wang, VOK Li, JCK Lam, Z Yu. CrowdTracker: Optimized urban moving object tracking using mobile crowd sensing. IEEE Internet of Things Journal 5 (5), 3452-3463, 2017.[14] T Wang, Z Wang, D Zhang, T Gu, H Ni, J Jia, X Zhou, and J Lv. Recognizing Parkinsonian Gait Pattern by Exploiting Fine-grained Movement Function Features. ACM Transactions on Intelligent Systems and Technology (TIST) 8 (1), 1-22, 2016.[15] Z Wang, C Chen, B Guo, Z Yu, and X Zhou. Internet Plus in China. IEEE IT Professional, Vol. 18, No. 3, pp. 5-8, 2016.[16] B Guo, Z Wang, Z Yu, Y Wang, N Yen, R Huang, and X Zhou. Mobile Crowd Sensing and Computing: The Review of an Emerging Human-Powered Sensing Paradigm. ACM Computing Surveys, Vol. 48, No. 1, Article No. 7, 2015.[17] Z Yu, Z Wang, H He, J Tian, X Lu, and B Guo. Discovering Information Propagation Patterns in Microblogging Services. ACM Transactions on Knowledge Discovery from Data (TKDD), Vol. 10, No. 1, Article No. 7, 2015.[18] Z Wang, D Zhang, X Zhou, D Yang, Z Yu, and Z Yu. Discovering and Profiling Overlapping Communities in Location Based Social Networks. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 44(4): 499-509, 2014.[19] Z Wang, X Zhou, D Zhang, D Yang, and Z Yu. Cross-Domain Community Detection in Heterogeneous Social Networks. Springer/ACM Journal of Personal and Ubiquitous Computing (PUC), 18(2): 369-383, 2014.[20] D Zhang, Z Wang, B Guo, and Z Yu. Social and Community Intelligence: Technologies and Trends. IEEE Software, 29(4): 88-92, 2012.2. 部分学术论文（会议）[1] H Zhang, Z Wang, Z Sun, W Song, Z Ren, Z Yu, and B Guo. Understanding the Mechanism of Through-Wall Wireless Sensing: A Model-based Perspective. In: Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2023).[2] C Liao, C Chen, S Guo, Z Wang, Y Liu, K Xu, D Zhang. Wheels Know Why You Travel: Predicting Trip Purpose via a Dual-Attention Graph Embedding Network. In: Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2022), Virtual.[3] D Ma, Z Wang, J Xie, Z Yu, B Guo, and X Zhou. Modeling Multivariate Time Series via Prototype Learning: a Multi-Level Attention-based Perspective. In: Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2020),  2020. (Best student paper award)[4] W Xu, ZW Yu, Z Wang, B Guo, Q Han. AcousticID: Gait-based Human Identification Using Acoustic Signal. In: Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2019), UK, 2019.[5] T Xin, B Guo, Z Wang, P Wang, JCK Lam, V Li, Z Yu. Freesense: a robust approach for indoor human detection using Wi-Fi signals. In: Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2018), Singapore, 2018.[6] B Guo, J Li, V Zheng, Z Wang, and Z Yu. CityTransfer: Transferring Inter- and Intra-City Knowledge for Chain Store Site Recommendation based on Multi-Source Urban Data. In: Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2018), Singapore, 2018.[7] Y Guo, B Guo, Y Liu, Z Wang, Y Ouyang, and Z Yu. CrowdSafe: Detecting Extreme Driving Behaviors based on Mobile Crowdsensing. In: Proceedings of the 14th IEEE International Conference on Ubiquitous Intelligence and Computing (UIC 2017), August 4-8, 2017, San Francisco, California, USA. (Best paper award)[8] P Wang, B Guo, T Xin, Z Wang, and Z Yu. TinySense: Multi-User Respiration Detection using Wi-Fi CSI Signals. In: Proceedings of the IEEE 19th International Conference on E-health Networking, Application & Services (HealthCom 2017), 2017.[9] T Xin, B Guo, Z Wang, M Li, and Z Yu. FreeSense: Indoor Human Identification with WiFi Signals. In: Proceedings of the 2016 IEEE Global Communications (GLOBECOM 2016), Washington, DC, USA, 2016.[10] T Wang, D Zhang, Z Wang, J Jia, H Ni and X Zhou. Recognizing Gait Pattern of Parkinson’s Disease Patients Based on Fine-Grained Movement Function Features. In: Proceedings of the 12th IEEE Conference on Ubiquitous Intelligence and Computing (UIC 2015), Beijing, China, 2015. (Best Paper Award)3. 专著（章节）[1] Z Yu, and Z Wang. Human Behavior Analysis: Sensing and Understanding. Springer, 2020.[2] Z Wang, X Zhou, D Zhang, B Guo, and Z Yu. Community Detection and Profiling in Location-based Social Networks. Creating Personal, Social, and Urban Awareness through Pervasive Computing, IGI Global, 158-175, 2013[3] B Guo, Y Liang, Z Wang, Z Yu, D Zhang, and X Zhou. Towards Personal, Social and Urban Awareness. Creating Personal, Social, and Urban Awareness through Pervasive Computing, IGI Global, 1-21, 2013[4] D Zhang, Z Yu, B Guo, and Z Wang. Exploiting Personal and Community Context in Mobile Social Networks. Mobile Social Networking: An Innovative Approach, Springer Verlag, 109-138, 2013 内容来自集群智慧云企服 实用新型专利1875代写全部资料全国受理

综合介绍

内容来自集群智慧云企服 实用新型专利1875代写全部资料全国受理