阎艳 - 北京理工大学 - 机械与车辆学院

个人简介

阎艳，女，1967年12月出生，北京理工大学机械工程专业博士，教授，博士生导师。曾任机械与车辆学院工业工程系科研副主任、学院副书记副院长、学院党委书记，现任校长助理、校党委教师工作部部长、校第三届学部委员。曾任国家国防科技工业局科学技术委员会委员、国防科技进步奖制造与材料专业组评审委员会委员、国防基础科研“十一五”、“十二五”规划数字化制造、先进设计组专家等。现任工业工程学会理事、国防基础科研“十三五”规划先进设计组专家、军委科技委基础研究制造技术组专家、计算机集成制造系统杂志理事、航空工艺研究所（625所）数控制造国防重点实验室学术委员会委员、航天八院兼职研究员及重大项目专家顾问等。长期从事数字化制造技术的基础及应用研究。主持或参与承担国防基础科研、总装预研、民用航天、国家自然基金、国防973项目等十余项；获国防科技进步奖一等奖1项，二等奖2项，三等奖4项；获北京市教学成果二等奖1项；获授权发明专利十余项，作为主编、副主编编写出版教材3本，参编出版专著2本；在国内外重要学术刊物上发表学术论文八十余篇，其中被SCI/EI收录六十余篇。2007年入选教育部新世纪优秀人才支持计划；2006年在国防科工委《关于表扬在国防科技工业中长期科技发展规划纲要编制中做出重要贡献的集体和个人的通报》中受到通报表扬；2005年获北京高校优秀德育工作者称号。代表性科研项目国家自然科学基金面上，多尺度产品基因驱动的设计过程与知识联动机制及方法研究，2014-2017 国防基础科研，分布式智力资源驱动的XXXX创新设计技术，2010-2013 北京市国际科技合作专项，人车协同与智能决策国际联合实验室建设，2019-2021 成果及荣誉国防科技进步奖一等奖（7）国防科技进步奖二等奖（4）国防科技进步奖三等奖（1）

研究领域

知识工程、优化设计与创新设计、智能决策

近期论文

查看导师最新文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

A function-based computational method for design concept evaluation; Advanced Engineering Informatics;2017(32):237-247; Jia Hao*, Qiangfu Zhao, Yan Yan. A Review of Tacit Knowledge: Current Situation and the Direction to Go; International Journal of Software Engineering and Knowledge Engineering; 27(5): 727-748; Jia Hao*, Qiangfu Zhao, Yan Yan, Guoxin Wang. An evolutionary computation based method for creative design inspiration generation; Journal of Intelligent Manufacturing; 30(4): 1673-1691；Jia Hao*, Yongjia Zhou, Qiangfu Zhao, Qing Xue. Characterizing the EEG Features of Inspiring Designers with Functional Terms; International Conference on Human-Computer Interaction; 10901: 371-381； Qian Zhang, Jia Hao*, Qing Xue, Yu Yan. Exploring the Impact of Functional Terms in Idea Generation in Design；International Conference on Computer in Engineering; 2018(12):1-13; Jia Hao*, Lu Wang, Ji Han, Dirk Schaefer. Evolutionary Neural Network-based Method for Constructing Surrogate Model with Small Scattered Dataset and Monotonicity Experience；International Conference on Soft Computing and Machine Intelligence；2018(5):43-38.Jia Hao*, Wenbin Ye, Guoxin Wang, Liangyue Jia. A rule-based method for automated surrogate model selection；Advanced Engineering Informatics；2020:45:101123; Liangyue Jia, Reza Alizadeh, Jia Hao*, Mistree Farrokh. Design optimization by integrating limited simulation data and shape engineering knowledge with Bayesian optimization (BO-DK4DO); Journal of Intelligent Manufacturing; 2020, Jia Hao*, Mengying Zhou, Guoxin Wang. Wang R, Wang G, Yan Y, et al. Ontology-based representation of meta-design in designing decision w orkflows[J]. ASME Journal of Computing and Information Science in Engineering, 2019, 19(1): 011003-19. Wang R, Nellippallil A B, Wang G, Yan Y, et al., Ontology-based uncertainty management approach in designing of robust decision workflows[J]. Journal of Engineering Design, 2019, 30: 726-757. Li P, Ren Y, Yan Y, et al. Intelligent product-gene acquisition method based on K-means clustering and mutual information-based feature selection algorithm[J]. Artificial Intelligence for Engineering Design Analysis and Manufacturing, 2019, 33(4): 469-483. Ming Z, Nellippallil A B, Yan Y, et al. PDSIDES—a knowledge-based platform for decision support in the design of engineering systems[J]. ASME Journal of Computing and Information Science in Engineering, 2018, 18(4): 041001-14. Ming Z, Wang G, Yan Y, et al. Ontology-based representation of design decision hierarchies[J]. ASME Journal of Computing and Information Science in Engineering, 2018, 18(1): 011001-12. Wang R, Nellippallil A B, Wang G, Yan Y, et al. Systematic design space exploration using a template-based ontological method. Advanced Engineering Informatics, 2018, 36: 163-177. Ming Z, Zeng C, Wang G, Yan Y, et al. Ontology-based module selection in the design of reconfigurable machine tools [J]. Journal of Intelligent Manufacturing, 2018, 1-17. DOI: 0.1007/s10845-018-1446-3 Huang S, Wang G, Shang X, Yan Y. Reconfiguration point decision method based on dynamic complexity for reconfigurable manufacturing system (RMS) [J]. Journal of Intelligent Manufacturing, 2018, 29(5): 1031-43. Ming Z, Wang G, Yan Y, et al. An ontology for reusable and executable decision templates[J]. ASME Journal of Computing and Information Science in Engineering, 2017, 17(3): 031008-13. Ming Z, Yan Y, Wang G, et al. Ontology-based executable design decision template representation and reuse [J]. AI EDAM - Artificial Intelligence for Engineering Design Analysis and Manufacturing, 2016, 30(4): 390-405.