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姓名:高超性别:
学历:博士
职称:教授
部门:网络工程系电话:13637990456
邮件地址:cgao@swu.edu.cn

研究方向:网络行为大数据挖掘与建模、网络结构与传播动力学、生物启发的人工智能算法





个人简介

辽宁人,北京工业大学工学博士(2006-2010),香港浸会大学博士后(2010-2012),德国柏林洪堡大学访问学者(2016-2017),硕士生导师


主要研究领域包括大数据下人类行为特征挖掘和经典人工智能复杂难计算问题求解:

1、数据驱动的复杂系统建模: (1)多源异构海量数据分析, 如基于社交媒体和公共交通数据的用户行为挖掘与情感计算; (2) 数据驱动的用户行为建模, 如突发事件中人类集群行为与情绪预测、基于网络结构的用户移动行为预测;

2、基于生物启发的群体智能算法研究: 多目标问题优化、分布式搜索、路径规划等人工智能领域复杂难计算问题求解;

3、复杂网络结构与传播动力学: 网络病毒与谣言传播控制、传播网络重构与传播源定位、网络行为异常检测与鲁棒性分析等。


教学情况

主讲课程:

本科生:《人工智能》(双语)、《数据结构与STL》(双语)、《面向对象程序设计C++》(双语)、《软件工程》、《Web信息系统开发》

研究生:《数据与知识工程》

 

教改项目:

主持:西南大学教育教学改革研究项目(2014JY064)。

参研:重庆市研究生教育教学改革研究项目(yjg110309)、重庆市优质课程《分布式系统》。


科研情况

主持项目:国家自然科学基金青年基金(61402379)、教育部博士点新教师基金(20120182120016)、重庆市自然科学基金(cstc2012jjA40013)、重庆市基础研究与前沿探索项目(cstc2018jcyjAX0274)、符号计算与知识工程教育部重点实验室开放基金(93K172014K02)、教育部中央高校基础业务费重点项目(XDJK2012B016)和重大项目(XDJK2016A008)、西南大学博士基金(SWU111024)。

参研项目:国家自然科学基金(60642003, 61403315)、北京市自然科学基金(4102007)、重庆市自然科学基金重点项目(cstc2012jjB40012)、重庆市基础与前沿研究计划项目(cstc2013jcyjA40022)、教育部中央高校基础业务费一般项目(XDJK2012C018)

Selected Publications:

1. Data analytics and data-driven complex systems modeling

• Xianghua Li, Jurgen Kurths, Chao Gao, et al., A hybrid algorithm for estimating origin-destination flowsIEEE Access, 2018, 6(1): 677-687 (IF=3.557, JCR-2)

• Zhanwei Du, Yongjian Yang, Chao Gao, et al., The temporal network of mobile phone users in Changchun Municipality Northeast China, Scientific Data, 2018, in press (IF=5.305)

• Xianghua Li, Zhen Wang, Chao Gao, Lei Shi, Reasoning human emotional response from large-scale social and public mediaApplied Mathematics and Computation, 2017, 310: 128-193  (ESI, IF=2.300, JCR-2)

• Yuxin Liu, Chao Gao, Zili Zhang, et al., A new multi-agent system to simulate the foraging behaviors of physarumNatural Computing, 2017,16(1):15-29(IF=0.860, CCF-C)

• Chao Gao, Jiming Liu, Network-based modeling for characterizing human collective behaviors during extreme eventsIEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017, 46(1):171-183 (IF=5.131)

• Chao Gao, Jiming Liu, Uncovering spatiotemporal characteristics of human online behaviors during extreme eventsPLoS ONE, 2015, 10(10): e0138673 (14 pages, IF=3.234)

• Chao Gao, Jiming Liu, Modeling and restraining mobile virus propagationIEEE Transactions on Mobile Computing, 2013, 12(3): 529-541 (IF=2.543, CCF-A)


2. Nature-inspired computing

• Chao Gao, Daniel Schenz, Xuelong Li, et al., Does being multi-headed make you better at solving problems? A survey of Physarum-based models and computationsPhysics of Life Reviews, 2018, doi: 10.1016/j.plrev.2018.05.002 (IF=13.840, JCR-1)

• Chao Gao, Zhengpeng Chen, Xianghua Li, et al., Multiobjective discrete particle swarm optimization for community detection in dynamic networksEPL(Europhysics Letters), 2018, 122(2): 28001 (IF=1.834, JCR-2) 

• Yuxin Liu, Chao Gao, Zili Zhang, et al., Solving NP-hard problems with physarum-based ant colony systemIEEE/ACM Transactions on Computational Biology and Bioinformatics, 2017,14(1):108-120(IF=2.428, CCF-C, JCR-2)

• Chao Gao, Shi Chen, Xianghua Li, et al., A physarum-inspired optimization algorithm for load-shedding problemApplied Soft Computing, 2017, 61: 239-255 (IF=3.541,JCR-2)

• Mingxin Liang, Chao Gao, Zili Zhang. A new genetic algorithm based on modified Physarum network model for bandwidth-delay constrained least-cost multicast routingNatural Computing, 2017,16(1):85-98(IF=0.757, CCF-C)

• Zili Zhang, Chao Gao, Yuxiao Lu, et al.,Multi-objective ant colony optimization based on the Physarum-inspired mathematical model for bi-objective traveling salesman problemsPLoS ONE, 2016, 11(1): e0146709. (23 pages, IF=3.234)
• Zili Zhang, Chao Gao, Yuxin Liu, et al., 
A universal optimization strategy for ant colony optimization algorithms based on the Physarum-inspired mathematical modelBioinspiration & Biomimetics, 2014, 9(3): 036006 (14 pages, IF=2.354) 


3. Complex network analytics

• Chao Gao, Zhen Su, Jiming Liu, Jurgen Kurths, Do central users always accelerate information diffusion? Communications of the ACM, 2018, in press (IF=3.063, JCR-1)

• Chao Gao, Mingxin Liang, Xianghua Li, et al., Network community detection based on the Physarum-inspired computational frameworkIEEE/ACM Transactions on Computational Biology and Bioinformatics, 2016, doi: 10.1109/TCBB.2016.2638824 (IF=2.428, CCF-C, JCR-2) 

• Zhen Su, Fanzhen Liu, Chao Gao, et al., Inferring infection rate based on observations in complex networksChaos, Solitons and Fractals, 2018, 107: 170-176 (IF=2.213)

• Chao Gao, Lu Zhong, Xianghua Li, et al., Combination methods for identifying influential nodes in networksInternational Journal of Modern Physics C, 2015, 26(6): 1550067 (20 pages, IF=1.260)

• Chao Gao, Jiming Liu, Ning Zhong, Network immunization with distributed autonomy-oriented entitiesIEEE Transactions on Parallel and Distributed Systems, 2011, 22(7):1222-1229 (IF=2.170, CCF-A)

• Chao Gao, Jiming Liu, Ning Zhong, Network immunization and virus propagation in email networks: experimental evaluation and analysisKnowledge and Information Systems, 2011, 27(2):253-279 (IF=2.639, CCF-B)
• Jiming Liu, Chao Gao, Ning Zhong, 
Autonomy-Oriented search in dynamic community networks: a case study in decentralized network immunizationFundamenta Informaticae, 2010, 99(2):207-226 (IF=0.717, CCF-C)


获奖情况

备注
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发布时间:2018-09-19 来源:本站原创 作者:本站编辑   浏览次数: