徐圆，博士，教授，博士生导师

徐圆，北京化工大学教授、博士生导师。现任北京自动化学会常务理事兼秘书长、中国化工学会信息技术应用专业委员会委员、中国自动化学会数据驱动控制、学习与优化专业委员会委员、中国人工智能学会不确定性人工智能专业委员会委员、中国人工智能学会可拓工程专业委员会委员、北京化工大学计算智能与系统工程研究所所长、以及国际期刊《Advances in Fuzzy Systems》 客座编辑。主要研究方向包括：智能建模与优化控制、故障检测与诊断、报警系统设计与优化、安全评价与应急救援、信息集成与虚拟现实等，主持国家重点研发计划子课题2项、国家自然科学基金项目3项、北京市自然科学基金项目1项、荣获首届北京市科协青年人才托举计划、2013北京高等学校“青年英才计划”、2013年度北京市优秀人才培养资助，同时主持软件开发环境国家重点实验室开放课题1项、测绘遥感信息工程国家重点实验室开放研究基金1项、中石油吉林石化分公司研究开发项目1项、联合主持国家自然科学基金项目1项、等，已发表相关学术论文100余篇，其中SCI/EI收录70余篇，授权发明专利5项，获批软件著作权4项。荣获1项省部级技术发明一等奖、1项省部级科技进步一等奖、1项省部级科技进步二等奖。

教学课程Teaching courses

主要科研项目 Research Projects

主要成果、奖励Main achievements（例如学术论文、教学名师、科技奖项等）

代表性论文

 [1]Yuan Xu, Cuihuan Fan, Qun-Xiong Zhu, Abbas Rajabifard, Nengcheng Chen, Yiqun Chen, and Yan-Lin He^*. Novel pattern matching integrated KCVA with adaptive rank-order morphological filter and its application to gault diagnosis. Industrial & Engineering Chemistry Research, 2019, DOI: 10.1021/acs.iecr.9b05403 (TOP SCI, JCRQ1, IF= 3.375)

 [2]Qun-Xiong Zhu, Zhong-Sheng Chen, Xiao-Han Zhang, Abbas Rajabifard, Yuan Xu^*, Yiqun Chen, Dealing with small sample size problems in process industry using virtual sample generation: a Kriging-based approach, Soft Computing, 2019, DOI: 10.1007/s00500-019-04326-3 (JCRQ3, IF= 2.784)

 [3] Meng, Q. Q. , Zhu, Q. X. , Gao, H. H. , He, Y. L. , Xu, Y.^ *. A novel scoring function based on family transfer entropy for bayesian networks learning and its application to industrial alarm systems. Journal of Process Control, 2019, 76: 122-132  (JCRQ3, IF= 3.316)

 [4] Yuan Xu, Sheng-Qi Shen, Yan-Lin He, Qun-Xiong Zhu^*. A novel hybrid method integrating CA-PCA with relevant vector machine for multivariate process monitoring. IEEE Transactions on Control Systems Technology, 2018,99 :1-8  (JCRQ2, IF= 5.371)

 [5]Zhu, Qun-Xiong; Zhang, Chen;  He, Yan-Lin;  Xu, Yuan^*. Energy modeling and saving potential analysis using a novel extreme learning fuzzy logic network: A case study of ethylene industry. Applied Energy, 2018, 213: 322-333  (TOP SCI, JCRQ1, IF= 8.426)

 [6]Yuan Xu, Mingqing Zhang, Liangliang Ye, Qun-Xiong Zhu, Zhiqiang Geng, Yanlin He, Yongming Han^*. A novel prediction intervals method integrating an error & self-feedback extreme learning machine with particle swarm optimization for energy consumption robust prediction. Energy, 2018, 164: 137-146 (TOP SCI, JCRQ1, IF= 5.537)

 [7]Yan-Lin He, Ping-Jiang Wang, Ming-Qing Zhang, Qun-Xiong Zhu, Yuan Xu^*. A novel and effective nonlinear interpolation virtual sample generation method for enhancing energy prediction and analysis on small data problem: A case study of Ethylene industry. Energy, 2018, 147 :418-427 (TOP SCI, JCRQ1, IF= 5.537)

 [8]Zhang, Xiao-Han ; Zhu, Qun-Xiong ; He, Yan-Lin; Xu, Yuan^*. Energy modeling using an effective latent variable based functional link learning machine. Energy, 2018, 162: 883-891  (TOP SCI, JCRQ1, IF= 5.537)

 [9] Zhang, Xiao-Han ; Zhu, Qun-Xiong; He, Yan-Lin; Xu, Yuan^*. A novel robust ensemble model integrated extreme learning machine with multi-activation functions for energy modeling and analysis: Application to petrochemical industry. Energy, 2018, 162: 593-602  (TOP SCI, JCRQ1, IF= 5.537)

 [10]Qun-Xiong Zhu, Xiao Wang, Yan-Lin He, Yuan Xu^*. An improved extreme learning machine integrated with nonlinear principal components and its application to monitoring complex chemical processes. Applied Thermal Engineering, 2018, 130: 745-753  (TOP SCI, JCRQ2, IF=4.026)

 [11]Yongming Han, Qunxiong Zhu, ZhiqiangGeng, Yuan Xu^*.Energy and carbon emissions analysis and prediction of complex petrochemical systems based on an improved extreme learning machine integrated interpretative structural model, Applied Thermal Engineering, 2017, 115: 280-291  (TOP SCI, JCRQ2, IF=3.771)

 [12]Yuan Xu, Mingqing Zhang, Qunxiong Zhu, Yanlin He^*. An improved multi-kernel RVM integrated with CEEMD for high-quality intervals prediction construction and its intelligent modeling application. Chemometrics and Intelligent Laboratory Systems, 2017, 171: 151-160  (JCRQ3, IF=2.701)

 [13]Zi-Qian Zhou, Qun-Xiong Zhu, Yuan Xu^*. Time series extended finite-state machine-based relevance vector machine multi-fault prediction. Chemical Engineering & Technology, 2017, 40 (4): 639-647  (JCRQ3, IF=1.588)

 [14]Han Liu, Gao Huihui, Xu Yuan^*, Zhu Qunxiong. Combining FAP, MAP and correlation analysis for multivariatealarm thresholds optimization in industrial process. Journal of Loss Prevention in the Process Industries. 2016, 40: 471-478  (JCRQ3, IF=1.818)

 [15]XU Yuan, YE Liangliang, ZHU Qunxiong^*. A new DROS extreme learning machine with differential vector KPCA approach for real-time fault recognition of nonlinear processes. Journal of Dynamic Systems. Measurement and Control, 2015. 137(5): 1101-1110  (JCRQ4, IF=0.975)

 [16]XU Yuan, ZHOU Ziqian, ZHU Qunxiong^*. A new feedback DE-ELM with time delay-based EFSM approach for fault prediction of non-linear process. Canadian Journal of Chemical Engineering, 2015, 93: 1603-1612  (JCRQ4, IF=1.066)

奖项与荣誉

 1. 石化企业虚拟现实应急救援演练与安全教育网络化智能系统，中国石油和化学工业联合会，项目鉴定，2017

 2. 基于工艺机理、专家知识和智能学习的延迟焦化装置优化控制技术，中国石油和化工自动化应用协会，技术发明奖，一等奖，2012

 3.基于数据驱动的大型石化装置智能优化运行技术及工程应用，中国石油和化工自动化应用协会，科技进步奖，一等奖，2010  

 4. PTA生产溶剂系统智能优化控制，中国石油和化学工业协会，科技进步奖，二等奖，2008

 5. 荣获中国自动化学会“优秀学会工作者”，2018

 6. 北京市科协系统“先进个人”，2017

 7. 荣获第十六届中国化工学会信息技术应用专业委员年会优秀论文，2017

 8. 第十四届北京化工大学“优秀青年主讲教师”，2016

 9. 第六届全国信息技术应用水平大赛“最佳指导老师”称号，2011

 10. 荣获第十二届中国化工学会信息技术应用专业委员会年会优秀论文一等奖 ，2009

 11.荣获The 3^rdInternational Symposium on Computational Intelligence and Industrial Applications最佳论文发表奖，2008