北京航空航天大学导师教师信息介绍简介-赖李媛君

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个人简历

赖李媛君，女，博士，2009年、2012年、2015年于北京航空航天大学自动化科学与电气工程学院获学士、硕士、博士学位，2016年1月至今任北京航空航天大学自动化科学与电气工程学院讲师。入选2016年中国科协青年人才托举工程计划，曾获国际仿真学会颁发的青年科学家奖，中国仿真学会优秀博士论文奖，三次获得北京航空航天大学优秀毕业生奖。目前研究方向包括可配置智能优化算法及其并行化，面向再制造的机器人拆卸建模与优化，多智能体系统动态模式发现与评估及自适应在线增量学习等。
围绕上述方向研究，已出版英文学术专著2部，发表学术论文30余篇，第一或通讯作者发表SCI论文9篇（其中ESI高被引论文1篇）。主持国家重点研发计划子课题1项，国家自然科学基金青年基金1项，参与国家自然科学基金面上项目2项。现为国际仿真学会（SCS）会员，中国仿真学会智能物联专委会委员，系国际期刊International Journal of Modeling, Simulation, and Scientific Computing副主编。
Yuanjun Laili received the B.S., M.S. and Ph.D. degree in Automation Science and Electrical Engineering from Beihang University, Beijing, China, in 2009, 2012 and 2015, respectively, and was awarded at each phase the outstanding graduate which was the highest honor for a student of the university. She is currently an Assistant Professor of the School of Automation Science and Electrical Engineering of Beihang University.
Her research interests include intelligent optimization theory and algorithms, modeling and simulation of complex system, robotic disassembly for remanufacturing and online incremental learning. She has managed 1 National Key Research and Development Program, 1 National Natural Science Foundation Project, and participated 2 National High-Tech Programs and 2 National Natural Science Foundation Project as a key researcher. Focusing on the multi-layer optimal-allocation of manufacturing resources, she established a comprehensive model to describe the macro-level service qualities and micro-level service dynamical behaviors in cloud environment. To implement high available, high accurate and high dependable optimal solver for dynamic objectives, she proposed the concept of configurable intelligent optimization algorithm and designed a number of upper-layer adaptive mechanisms for the under-layer parameter, operator and algorithm configurations. Furthermore, she has carried out research on the parallel optimization algorithm and presented a new reflex migration mechanism for the adaptation of parallel topology, which can generally improve the whole efficiency of optimal-decision by at least 2-5 times. She has also been very active with knowledge transfer to industry, applying the results of her work to help multi-disciplinary companies to implement intelligent pattern recognition and optimal decision.
Based on these works, she has co-authored the books “Configurable Intelligent Optimization Algorithm – Design and Practice in Manufacturing”, "Model Engineering in Simulation", published more than 30 papers in international peer-reviewed journals or conferences (with over 710 citations). One of her publications was elected by Thomson Reuters to “Essential Science Indicators” (ESI) with 171 citations.
She has been won the “Young Talent Lift Project” (2016) supported by China Association for Science and Technology and the “Young Simulation Scientist Award” from the Society for Modeling and Simulation International (SCS). This project is highly competitive and support less than 200 young researchers out of more than 4000 applicants every year. Besides, she has been awarded various honors including“Young Simulation Scientist Award” (2017),“Excellent doctorate theses of Chinese Association for System Simulation” (2015), “Outstanding graduate of Beihang University” (2015), “National Scholarship for PhD students” (2014), “Doctoral Student Innovation Fund of Beihang University” (2014) and “Best paper award of Chinese Association for System Simulation” (2016), “Outstanding graduate dissertation of Beihang University” (2012), “Outstanding undergraduate dissertation of Beihang University” (2009).
She is a Member of SCS and a commitee memberof the Commitee of Intelligent Networked Things (CINT)in China Simulation Federation (CSF). During the last five years, she organized many academic exchange activities as an very active member of the SCS student branch and serves as one of the young representatives of MISS (McLeod Institute of Simulation Science) Beihang Center. She has also served as a workshop chair of “UV2018”,“AsiaSim/SCS AutumnSim 2016” and committee member of“Chinese Simulation Conference 2018”, “Chinese Simulation Conference 2017”, “AsiaSim 2015”, “CINT2015” and “CINT2013”. Now she serves as an editor of “International Journal of Modeling, Simulation, and Scientific Computing”and reviewer of“SIMULATION: Transactions of The Society for Modeling and Simulation International”, “Computers in Industry”, “IEEE Transactions on Systems, Man and Cybernetics”, “European Journal of Operational Research”, and so on.

教育经历

工作经历

[1] 2017.7-2018.7
伯明翰大学 |访问学者

[2] 2016.1-至今
北京航空航天大学 |讲师 |在职

研究方向

[1] 可配置智能优化算法及其并行化

[2] 面向再制造的机器人拆卸建模与优化

[3] 多智能体系统动态模式发现与评估

[4] 自适应在线增量学习

团队成员

北航云制造技术研究中心
北航智能制造与仿真技术实验室
复杂产品先进制造系统教育部工程研究中心

研究领域

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［1］可配置智能优化算法及其并行化
［2］面向再制造的机器人拆卸建模与优化
［3］多智能体系统动态模式发现与评估
［4］自适应在线增量学习

开授课程

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科研项目

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[1] 中国科协青年托举人才工程计划项目, 在研
[2] 数据驱动的云数据中心智能管理技术与平台子课题“数据驱动的任务群动态并合调度技术研究”, 在研, 国家重点研发计划
[3] 多智能体仿真模型演化特征关系挖掘及可信度评估方法研究, 在研, 国家自然基金青年基金

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论文

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[1] Zhang L, Zeigler B P, Laili Y.Model Engineering for Simulation.Elsevier.2018
[2] Tao F, Zhang L, Laili Y.Configurable Intelligent Optimization Algorithm.Springer.2016
[3] Laili Y,Tao F,Pham D T,Wang Y,Zhang L.Robotic disassembly re-planning using a two-pointer detection strategy and a super-fast bees algorithm.Robotics and Computer-Integrated Manufacturing.2019,52 :130-142
[4] Laili Y,Zhang L,Li Y.Parallel transfer evolution algorithm.Applied Soft Computing.2019,75 :686-701
[5] Laili Y, Tao F, Wang F, Zhang L, Lin T.An Iterative Budget Algorithm for Dynamic Virtual machine consolidation under cloud computing environment.IEEE Transactions on Services Computing.2018
[6] Laili Y,Zhang L,Luo Y.Pattern-based Validation Metric for Simulation Models.SCIENCE CHINA Information Sciences.2019
[7] Laili Y, Zhang L, Tao F, Ma P.Rotated neighbor learning-based auto-configured evolutionary algorithm.Science China Information Sciences.2016,59 (5):052101
[8] Laili Y, Tao F, Zhang L, Cheng Y, Luo Y, Sarker B R.A ranking chaos algorithm for dual scheduling of cloud service and computing resource in private cloud.Computers in Industry.2013,64 (4):448-463
[9] Laili Y, Tao F, Zhang L, Sarker B R.A study of optimal allocation of computing resources in cloud manufacturing systems.The International Journal of Advanced Manufacturing Technology.2012,63 (5-8):671-690
[10] Liu A, Laili Y.Balance Gate Controlled Deep Neural Network.Neurocomputing.2018
[11] Tao F, LaiLi Y, Xu L, Zhang L.FC-PACO-RM: a parallel method for service composition optimal-selection in cloud manufacturing system.IEEE Transactions on Industrial Informatics.2013,9 (4):2023-2033
[12] Tao F, Laili Y, Liu Y, Feng Y, Wang Q, Zhang L, Xu L.Concept, principle and application of dynamic configuration for intelligent algorithms.IEEE systems journal.2014,8 (1):28-42
[13] Tao F, Laili Y, Zhang L, Zhang Z, Nee A C.QMAEA: a quantum multi-agent evolutionary algorithm for multi-objective combinatorial optimization.Simulation.2014,90 (2):182-204
[14] Fang Y,Ming H,Li M,Liu Q,Pham D T.Evolutionary many-objective optimization for mixed-model disassembly line balancing with multi-robotic workstations :1-17
[15] Tao F, Li C, Liao T W, Laili Y.BGM-BLA: a new algorithm for dynamic migration of virtual machines in cloud computing.IEEE Transactions on Services Computing.2016,9 (6):910-925
[16] Zhang Y, Tao F, Laili Y, Hou B, Lv L, Zhang L.Green partner selection in virtual enterprise based on Pareto genetic algorithms.The international journal of advanced manufacturing technology.2013,67 (9-12):2109-2125
[17] Laili Y, Tao F, Zhang L, Ren L.The optimal allocation model of computing resources in cloud manufacturing system.2011 Seventh International Conference on Natural Computation (ICNC).2011,4 :2322-2326
[18] Zhou L, Zhang L, Ren L, Laili Y.Matching and selection of distributed 3D printing services in cloud manufacturing.Industrial Electronics Society, IECON 2017-43rd Annual Conference of the IEEE..2017 :4728-4733
[19] Li F, Zhang L, Laili Y.Multi-Task Scheduling Based on QoS Evaluation in Cloud Manufacturing System.ASME 2017 12th International Manufacturing Science and Engineering Conference.2017
[20] Li F, Laili Y, Zhang L, Hu X, Zeigler B P.Service composition and scheduling in cloud-based simulation environment.Proceedings of the Model-driven Approaches for Simulation Engineering Symposium.2018

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荣誉及奖励

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[1]中国仿真学会优秀博士论文
[2]Young Simulation Scientist Award

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