个人简介
马海平，男，1981年生，浙江诸暨人，工学博士，博士后，教授，硕士生导师，浙江省高校中青年学科带头人，校中青年学术骨干，英国女王大学公派访问****。2004年7月获绍兴文理学院物理学学士学位，2007年7月获太原理工大学控制理论与控制工程硕士学位，2014年11月获上海大学控制理论与控制工程博士学位，其博士论文获中国仿真学会优秀博士学位论文。2015年11月至2017年11月在浙江大学工业控制技术国家重点实验室网络传感与控制研究组从事博士后研究，期间2016年11月至2017年11月在英国女王大学以公派访问****身份进行学术交流。2007年8月起至今，一直在绍兴文理学院数理信息学院从事教学和科研工作，多次获得校级先进个人和优秀教师。教学方面主讲课程为人工智能导论、专业英语等专业基础课，科研方面主要研究方向为智能计算，智能控制与信息处理等。主持国家自然科学基金项目2项（**，**），主持省自然科学基金项目2项（Y**，LY 19F 030011），主持市公益性技术应用研究计划项目1项（2013B70004），排名第3参与国家自然科学基金项目1项，获浙江省自然科学基金优秀论文奖1项，校级科研成果一等奖1项、二等奖1项。以第一作者在John Wiley & Sons出版英文专著1本，在国内外权威期刊上以第一作者发表SCI论文30余篇，单篇SCI他引最高170次，相关成果Google Scholar他引已超1300次，授权国家发明专利4项。同时指导国家级大学生创新创业训练计划项目1项（1），浙江省大学生科技创新活动计划暨新苗人才计划项目3项（2014R426007、2015R428029、2016R428027）。现担任中国仿真学会生命系统建模仿真专业委员会委员，波兰国家自然科学基金项目通讯评议专家，30多种SCI国际期刊审稿人。

工作经历
2021.01-至今：绍兴文理学院数理信息学院教授
2016.01-2020.12：绍兴文理学院数理信息学院副教授
2016.11-2017.11：英国贝尔法斯特女王大学信息研究中心公派访问****
2015.11-2017.11：浙江大学工业控制技术国家重点实验室博士后
2011.01-2015.12：绍兴文理学院数理信息学院讲师
2007.09-2010.12：绍兴文理学院数理信息学院助教

教育背景
2011.09-2014.11：上海大学机自学院控制理论与控制工程专业工学博士学位
2004.09-2007.07：太原理工大学自动化学院控制理论与控制工程专业工学硕士学位
2000.09-2004.07：绍兴文理学院数理信息学院物理学专业理学学士学位

研究兴趣
智能计算及应用，智能控制与信息处理，滤波算法与估计理论，嵌入式系统设计

出版专著
Haiping Ma and Dan Simon, Evolutionary Computation with Biogeography-based Optimization, JohnWiley & Sons, 2017.01 （ISBN：79）

科研项目
浙江省自然科学基金项目：多系统优化方法及在电池充电策略设计中的应用研究（编号：LY 19F 030011），2019-01至2021-12，主持人
国家自然科学基金项目：进化计算的演化机理分析及在大规模不确定优化中的应用研究（编号：**），2017-01至2017-12，主持人
国家自然科学基金项目：生物地理学智能同步优化算法及其在下肢假肢中的应用研究（编号：**），2014-01至2016-12，主持人
浙江省自然科学基金项目：岛屿生态学优化算法的关键技术及其在多关联复杂系统中的应用研究（编号：Y**），2010-01至2011-12，主持人
绍兴市应用研究计划项目：网络化智能高端数字喷墨印花控制系统研制（编号：2013B70004），2013-01至2015-06，主持人
国家自然科学基金项目：面向恶意程序传播的异质传感网可靠度评估和主动防御策略研究（编号：**），2018-01至2021-12，参与
国家自然科学基金项目：球面散乱数据建模的神经网络方法（编号：**），2012-01至2015-12，参与

所获奖励
中国仿真学会优秀博士学位论文，2015.12
浙江省自然科学基金优秀论文奖，2012.10
绍兴文理学院自然科学类成果二等奖，2015.06
绍兴文理学院自然科学类成果一等奖，2012.06

指导学生
国家级大学生创新创业训练计划项目：基于无线传感网络的废水污染源在线监测系统研发（编号：1），2015.01-2016.12，指导老师
浙江省大学生科技创新活动计划暨新苗人才计划项目：基于组合MEMS传感器识别的数据手套设计（编号：2016R428027），2016.01-2017.06，指导老师
浙江省大学生科技创新活动计划暨新苗人才计划项目：基于机器视觉的曲轴止推片质量检测系统研发（编号：2015R428029），2015.01-2016.06，指导老师
浙江省大学生科技创新活动计划暨新苗人才计划项目：基于物联网的智能楼宇节能监控系统研发（编号：2014R426007），2014.01-2015.06，指导老师

发明专利
马海平，潘张鑫，卢新祥，锂离子电池充电优化方法（专利号：ZL6.7），2020.11.13
马海平，陆伟奇，一种通过多参数融合处理设备状态的方法和系统（专利号：ZL 1.0），2018.05.29
马海平，陆伟奇，叶森钢，数字印花机用墨色快速控制方法及其控制系统（专利号：ZL1.9），2016.05.11
王春早，马海平，张斌，绝缘栅双极型晶体管（专利号：ZL 8.X），2017.01.04

期刊论文
[1] Haiping Ma*, Minrui Fei, Zheheng Jiang, LingLi, Huiyu Zhou, and Danny Crookes, “A multi-population based multi-objectiveevolutionary algorithm”, IEEETransactions on Cybernetics, 2020, 50 (2): 689-702.
[2] Haiping Ma*, Chao Sun, Jinglin Wang, ZhileYang and Huiyu Zhou, “Multi-system optimization for an integrated productionscheduling with resource saving problem in textile printing and dyeing”, Complexity,2020, Article ID: **.
[3] Haiping Ma*, Shigen Shen, Mei Yu, Zhile Yang,Minrui Fei, and Huiyu Zhou, “Multi-population techniques in nature inspiredoptimization algorithms: A comprehensive survey”, Swarm and Evolutionary Computation, 2019, 44: 365-387.
[4] Haiping Ma*, Dan Simon, Patrick Siarry, ZheliYang, and Minrui Fei, “Biogeography-based optimization: A 10-year review”, IEEE Transactions on Emerging Topics in ComputationalIntelligence, 2017, 1 (5): 391-407.
[5] Haiping Ma, Zhile Yang*, Pengcheng You, and Minrui Fei, “Multi-objectivebiogeography-based optimization for dynamic economic emission load dispatchconsidering plug-in electric vehicles charging”, Energy, 2017, 135: 101-111.
[6] Haiping Ma*, Sengang Ye, Dan Simon, andMinrui Fei, “Conceptual and numerical comparisons of swarm intelligence optimizationalgorithms”, Soft Computing, 2017, 21(11): 3081-3100.
[7] Haiping Ma*, Dan Simon, Minrui Fei and Hongwei Mo ,“Interactive Markov models of optimization searchstrategies”, IEEE Transactions onSystems, Man, and Cybernetics: Systems, 2017, 47 (5): 808-825.
[8] Haiping Ma*, Dan Simon and Minrui Fei, “Statistical mechanics approximationof biogeography-based optimization”, EvolutionaryComputation, 2016, 24 (3): 427-458.
[9] Haiping Ma*, Minrui Fei, and Zhile Yang,“Biogeography-based optimization for identifying promising compounds inchemical process”, Neurocomputing,2016, 174: 494-499.
[10] Haiping Ma*, Shufei Su, Dan Simon, and Minrui Fei, “Ensemble multi-objective biogeography-basedoptimization with application to automated warehouse scheduling”, EngineeringApplications of Artificial Intelligence, 2015, 44: 79-90.
[11] Haiping Ma*, Minrui Fei, Dan Simon, and Hongwei Mo , “Update-based evolutioncontrol: A new fitness approximation method for evolutionary algorithms”, Engineering Optimization, 2015, 47(9):1177-1190.
[12] Haiping Ma*, Minrui Fei, DanSimon, and Zixiang Chen, “Biogeography-based optimization in noisy environments”,Transactions of the Institute ofMeasurement and Control, 2015, 37(2): 190-204.
[13] Haiping Ma*, Dan Simon, Minrui Fei, Xinzhan Shu, and Zixiang Chen, “Hybrid biogeography-basedevolutionary algorithms”, Engineering Applications of ArtificialIntelligence, 2014, 30: 213-224.
[14] Haiping Ma*, DanSimon, and Minrui Fei, “On the convergence of biogeography-based optimizationfor binary problems”, MathematicalProblems in Engineering, 2014, Article ID: 147457.
[15] Haiping Ma*, Minrui Fei, Zhile Yang, Haikuan Wang, “Wireless networked learningcontrol system based on Kalman filter and biogeography-based optimization method”,Transactions of the Institute ofMeasurement and Control, 2014, 36 (2): 224-236.
[16] Haiping Ma*, Dan Simon, Minrui Fei, and Zixiang Chen, “On the equivalences anddifferences of evolutionary algorithms”, EngineeringApplications of Artificial Intelligence, 2013, 26 (10): 2397-2407.
[17] Haiping Ma*, DanSimon, Minrui Fei and Zhikun Xie, “Variations of biogeography-based optimizationand Markov analysis”,Information Sciences, 2013, 220 (1): 492-506.
[18] Haiping Ma*, Xieyong Ruan and Zhangxin Pan, “Handling multiple objectives with biogeography-basedoptimization”, International Journal of Automationand Computing. 2012, 9 (1): 30-36.
[19] Haiping Ma* andDan Simon, “Analysisof migration models of biogeography-based optimization using Markov theory”, Engineering Applications of Artificial Intelligence, 2011, 24 (6): 1052-1060.
[20] Haiping Ma* and Dan Simon, “Blended biogeography-basedoptimization for constrained optimization”, EngineeringApplications of Artificial Intelligence, 2011, 24 (3): 517-525.
[21] Haiping Ma*, Xieyong Ruan and Zhangxin Pan, “Genetic interacting multiple modelalgorithm based on H∞filter for maneuvering target tracking”, International Journal of Control, Automation, and Systems, 2011, 9 (1):125-131.
[22] Haiping Ma*, “An analysis of the equilibrium of migration models for biogeography-basedoptimization”, Information Sciences,2010, 180 (18): 3444-3464.
[23] Haiping Ma*,Xue Li, and ShengdongLin, “Analysis of migration rate models for biogeography-based optimization”, Journal of Southeast University (Natural Science Edition), 2009, 39 (S1):16-21.
[24] 马海平*, 朱聪, 母佳鑫, 孙超, 求解复杂耦合问题的多系统优化方法, 控制理论与应用, 2020,37 (11): 2301-2310.
[25] 马海平*, 李寰, 阮谢永, 一种群体迁移优化算法及性能分析, 控制理论与应用, 2010, 27 (3): 329-334.
[26] 马海平*, 陈子栋, 潘张鑫, 一类基于物种迁移优化的进化算法, 控制与决策, 2009, 24 (11): 1620-1624.
[27] 马海平*, 阮谢永, 朱敏杰, 金宝根, 道路条件下车辆跟踪的鲁棒H∞滤波算法, 电子学报, 2008, 36 (12): 2363-2366.
[28] 马海平*, 陈子栋, 一种基于H∞滤波的模糊变结构交互多模型算法, 电子学报, 2008, 36 (2): 245-249.
[29] Yadong Yu, Haiping Ma*, MeiYu, Sengang Ye, and Xiaolei Chen, “Multi-population management in evolutionaryalgorithms and application to complex warehouse scheduling problems”, Complexity, 2018, Article ID: **.
[30] Sengang Ye, Haiping Ma*,Sheng Xu, Wenqiang Yang and Minrui Fei, “An effective fireworks algorithm forwarehouse-scheduling problem”, Transactionsof the Institute of Measurement and Control, 2017, 39 (1): 75-85.
[31] Zheheng Jiang, Danny Crookes, Brian D. Green, Yunfeng Zhao, HaipingMa, Ling Li, Shengping Zhang, Dacheng Tao, and Huiyu Zhou, “Context-awaremouse behavior recognition using hidden Markov models”, IEEE Transactions onImage Processing, 2019, 28 (3): 1133-1148.
[32] Kailong Liu, Kang Li, HaipingMa, Jianhua Zhang, and Qiao Peng, “Multi-objective optimization of chargingpatterns for lithium-ion battery management”, Energy Conversion and Management, 2018, 159: 151-162.
[33] Zhile Yang, Kang Li, Yuanjun Guo, Haiping Ma, and Min Zheng, “Compactreal-valued teaching-learning based optimization with the applications toneural network training”, Knowledge-BasedSystems, 2018, 159: 51-62.
[34] Shigen Shen, Haiping Ma,En Fan, Keli Hu, Shui Yu, Jianhua, Liu, and Qiying Cao, “A non-cooperativenon-zero-sum game-based dependability assessment of heterogeneous WSNs withmalware diffusion”, Journal of Networkand Computer Applications, 2017, 91: 26-35.

会议论文
[35] Haiping Ma*, Pengcheng You, Kailong Liu, Zhile Yang, andMinrui Fei, “Optimal battery charging strategy based on complex systemoptimization”, 2017International Conference on Life System Modeling and Simulation &International Conference on Intelligent Computing for Sustainable Energy andEnvironment,Nanjing, China, 2017: 371-378.
[36] Haiping Ma*, Zhile Yang, Pengcheng You andMinrui Fei, “Complex system optimization for economic emission load dispatch”, 11th UKACC International Conference onControl, Belfast, UK, 2016: 1-6.
[37] Haiping Ma*, Minrui Fei, and Zhiguo Ding, “Biogeography-based optimization withensemble of migration models for global numerical optimization”, 2012 IEEE World Congress on ComputationalIntelligence (WCCI), Brisbane, Australia, 2012: 2981-2988.
[38] Haiping Ma*, Xieyong Ruan and Baogen Jin, “Oppositional ant colony optimizationalgorithm and its application to fault monitoring”, Proceedings of the 29th Chinese Control Conference, Beijing, China,2010: 1238-1242.
[39] Haiping Ma* andDan Simon, “Biogeography-based optimization with blendedmigration for constrained optimization problems”, Proceedings of the Genetic and Evolutionary Computation Conference(GECCO), Portland , Oregon , USA , 2010: 417-418.
[40] Haiping Ma*, Shengdong Lin andBaogen Jin, “Oppositional particle swarm optimizationalgorithm and its application to fault monitor”, Proceedings of the 2009 Chinese Conference on Pattern Recognition, Nanjing , China ,2009: 458-462.
[41] Haiping Ma*, Suhong Ni and ManSun, “Equilibrium species counts and migration modeltradeoffs for biogeography-based optimization”, Proceedings of the48th IEEEConference on Decision and Control and 28th Chinese Control Conference,Shanghai, China, 2009: 3306-3310.

学术兼职（审稿）
IEEETransactions on Cybernetics
IEEETransactions on Evolutionary Computation
IEEETransactions on Industrial Electronics
IEEETransactions on Vehicular Technology
IEEETransactions on Mechatronics
IEEECommunications Letters
IEEE/CAA Journalof Automatica Sinica
InformationSciences
Applied Soft Computing
Swarm andEvolutionary Computation
EngineeringApplication of Artificial Intelligence
Soft Computing
Neurocomputing
EngineeringOptimization
Transactions ofthe Institute of Measurement and Control
MathematicalProblems in Engineering
AerospaceScience and Technology
AppliedMathematics and Computation
Systems Scienceand Control Engineering
Control andDecision
Control Theoryand Application
InternationalJournal of Computer Aided Engineering and Technology
Journal ofApplied Mathematics
Journal ofNetwork and Computer Application
……