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基本信息
姓 名： 冯亮
性 别： 男
职 称： ****引进人才、教授(博导，硕导)
职 务：
电 话：
办公地点：
E-mail： liangf<@>cqu.edu.cn / brightfengs<@>gmail.com
研究方向： 智能计算，大数据挖掘与优化，多任务优化，机器学习，多智能体系统等
招生信息：年度招收博士生1名、硕士生4名，课题组与国内外知名高校、研究机构及IT企业合作紧密，欢迎计算机、软件、数学及自动化等相关专业同学申请加入课题组。
招收弘深青年教师（特别资助：37-40万元/年，重点资助：27-30万元/年）

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个人简介：
冯亮为重庆大学“****”引进人才、教授、博士生导师、入选重庆市****引进人才、重庆市学术带头人后备人才、新加坡南洋理工大学博士。先后在南洋理工智能计算实验中心，多平台游戏创新中心，以及新加坡A*Star南洋理工联合复杂系统实验室从事研究工作。研究方向包括（但不局限于）智能计算，大数据挖掘与优化，机器学习，以及多智能体系统等。获得IEEE Congress on Evolutionary Computation 2012 最佳学生论文提名、2019 IEEE Transactions on Evolutionary Computation 杰出论文奖。担任IEEE Transactions on Emerging Topics in Computational Intelligence、IEEE Computational Intelligence Magazine、Memetic Computing Journal、Cognitive Computing Journal副主编。 IEEE智能计算协会Task force on transfer learning and transfer optimization 创办主席。

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代表性论文（*通信作者）
Huang, L. Feng*, A. K. Qin, M. Chen, and K. C. Tan, "Towards Large-Scale Evolutionary Multi-Tasking: A GPU-Based Paradigm",IEEE Transactions on Evolutionary Computation, In press, 2021.
L. Zhou, L. Feng*, A. Gupta, and Y. S. Ong, “Learnable Evolutionary Search across Heterogeneous Problems via Kernelized Autoencoding”, IEEE Transactions on Evolutionary Computation, 25(3), 567-581, 2021.
K. C. Tan, L. Feng* and M. Jiang, "Evolutionary Transfer Optimization - A New Frontier in Evolutionary Computation Research," IEEE Computational Intelligence Magazine, vol. 16, no. 1, pp. 22-33, Feb. 2021
L. Feng*, Y. Huang, I. Tsang, A. Gupta, K. Tang, K. C. Tan and Y. S. Ong, "Towards Faster Vehicle Routing by Transferring Knowledge From Customer Representation," IEEE Transactions on Intelligent Transportation Systems, In Press, 2021.
L. Feng*, Y. Huang, L. Zhou, J. Zhong, A. Gupta, K. Tang, and K. C. Tan, “Explicit Evolutionary Multitasking for Combinatorial Optimization: A Case Study on Capacitated Vehicle Routing Problem”, IEEE Transactions on Cybernetics, 51(6), 3143-3156, 2020.
L. Feng*, W. Zhou, W. Liu, Y. -S. Ong and K. C. Tan, "Solving Dynamic Multiobjective Problem via Autoencoding Evolutionary Search," IEEE Transactions on Cybernetics, In press, 2020.
L. Feng*, L. Zhou, A. Gupta, J. Zhong, Z. Zhu, K. C. Tan and K. Qin, "Solving Generalized Vehicle Routing Problem With Occasional Drivers via Evolutionary Multitasking,", IEEE Transactions on Cybernetics, In press, 2019.
L. Feng*, L. Zhou, J. Zhong, A. Gupta, Y. S. Ong and K. C. Tan, "Evolutionary Multitasking via Explicit Autoencoding,", IEEE Transactions on Cybernetics, Vol. 49, No. 9, pp. 3457-3470, 2019.
L. Feng*, Y. S. Ong, S. Jiang and A. Gupta, "Autoencoding Evolutionary Search with Learning across Heterogeneous Problems", IEEE Transactions on Evolutionary Computation, Vol. 21, No. 5, pp. 760 - 772, 2017.
L. Feng*, Y.-S. Ong, M.-H. Lim, and Ivor W. Tsang. "Memetic Search with Inter-Domain Learning: A Realization between CVRP and CARP", IEEE Transactions on Evolutionary Computation, Vol. 19, No. 5, pp. 644-658, 2015.
L. Zhou, L. Feng*, K. C. Tan and J. Zhong, Z. Zhu, K. Liu and C. Chen, “Toward Adaptive Knowledge Transfer in Multifactorial Evolutionary Computation”, IEEE Transactions on Cybernetics, In press, 2020.
Y. Hou, Y. S. Ong, L. Feng* and J. M. Zurada, "An Evolutionary Transfer Reinforcement Learning Framework for Multi-Agent System", IEEE Transactions on Evolutionary Computation, Vol. 21, No. 4, pp. 601-615, 2017, 2017.
J. Zhong, L. Feng*, W. Cai , and Y. S. Ong, "Multifactorial Genetic Programming for Symbolic Regression Problems", IEEE Transactions on Systems, Man, and Cybernetics: System, In press, 2018
J. Zhong, L. Feng*, and Y. S. Ong, "Gene Expression Programming: A Survey", IEEE Computational Intelligence Magazine, 12(3), 54-72, 2017
A. Gupta, Y.-S. Ong and L. Feng, "Multifactorial Evolution: Towards Evolutionary Multitasking", IEEE Transactions on Evolutionary Computation, Vol. 20, No. 3, pp. 343-357, 2016. (获得2019该期刊Outstanding Paper Award)
J. Liu, Y. Cao, Y. Xue, D. Li, L. Feng*, & Y. F. Chen, Automatic unit layout of masonry structure using memetic algorithm and building information modeling. Automation in Construction, 130, 103858, 2021
J. Liu, P. Liu, L. Feng*, W. Wu, D. Li, & Y. F. Chen, Automated clash resolution for reinforcement steel design in concrete frames via Q-learning and Building Information Modeling. Automation in Construction, 112, 103062, 2020
A. Gupta, Y. Ong and L. Feng, "Insights on Transfer Optimization: Because Experience is the Best Teacher," IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 2, no. 1, pp. 51-64, Feb. 2018
A. Gupta, Y. Ong, L. Feng and K. C. Tan, "Multiobjective Multifactorial Optimization in Evolutionary Multitasking," IEEE Transactions on Cybernetics, vol. 47, no. 7, pp. 1652-1665, July 2017
X. Xue, K. Zhang, K. C. Tan, L. Feng, J. Wang, et al. Affine transformation-enhanced multifactorial optimization for heterogeneous problems. IEEE Transactions on Cybernetics, In press, 2020

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专著：

L. Feng, Y. Hou, Z. Zhu (2021) Optinformatics Across Heterogeneous Problem Domains and Solvers. In: Optinformatics in Evolutionary Learning and Optimization. Adaptation, Learning, and Optimization, vol 25. Springer, Cham.
周绪红、刘界鹏、冯亮等，建筑智能建造技术初探及其应用，中国建筑工业出版社，2021

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部分科研项目：

国家军委科技委，创新特区项目，xxxxxx，（负责）
国家自然科学基金面上基金信息科学部资助项目: 基于迁移学习的智能多任务高性能优化算法研究。（负责）
国家自然科学青年基金信息科学部资助项目：基于迁移学习和模因计算的智能交通路径规划研究。(负责)
重庆市科技计划项目基础科学与前沿技术研究专项资助项目：基于数据挖掘和模式识别的智能交通路径规划研究。（负责）
重庆大学中央高校基本科研业务费专项资助项目: 面向智慧城市物流的智能路径优化算法研究。（负责）
重庆市人社局留创项目资助：进化多任务智能优化算法研究。（负责）
重庆大学学科交叉项目：建筑业大数据与人工智能。（次负责）

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学术服务

电机电子工程师学会通信协会（IEEE）以及IEEE计算智能协会成员
ACM会员及ACM重庆分部秘书
中国计算机协会会员；中国计算机协会智能仿真优化与调度专委会委员
IEEE CIS Task Force on "Transfer Learning & Transfer Optimization", 创始主席
担任国际期刊IEEE Transactions on Emerging Topics in Computational Intelligence、IEEE Computational Intelligence、Memetic Computing Journal 及Cognitive Computing Journal 副主编
担任2016、2017、2018、2019及2020多个国际智能计算大会（IEEE CEC）专题主席；担任2017、2018、2019及2020国际智能计算大会（IEEE CEC）多任务优化竞赛主席
担任多个国际会议如AAAI、IJCAI、IEEE CEC、ACM GECCO，等评议委员会委员；担任多个国际顶级期刊如IEEE TEVC，IEEE Cybernetics、MIT ECJ、IEEE TNNLS等评审。