凌光

更新时间:2023-09-21

一、个人基本情况

姓名:凌光

性别:男

出生年月:1980.10

职称/职务:副教授/系副主任

学位/学历:博士/研究生

/博士生导师:硕导

联系方式:ling_guang0@163.com

研究方向:数据科学与统计应用、大数据分析与处理,复杂网络系统分析


二、教育背景与工作经历

2001/09–2005/07,武汉理工大学,信息与计算科学专业,学士

2005/09–2007/06,华中科技大学,概率论与数理统计专业,硕士研究生

2012/09–2016/06,华中科技大学,控制科学与工程专业,博士研究生

2016/09–2018/09,武汉理工大学,统计学系,讲师

2018/10–现在,武汉理工大学,统计学系,副教授,硕导


三、教学研究

主持武汉理工大学研究生课程资源库建设项目1项,研究生案例教学库建设项目1项,本科生“课程思政”建设项目1项,研究生“课程思政”示范课程项目1项,本科教学改革研究项目1项,研究生教育教学改革研究校级重点项目1项;参与在线开放课程建设项目2项,课程教学团队1门,湖北省教育教学改革研究项目1项。

全国大学生市场调查与分析大赛优秀指导教师,历年来指导学生参加全国大学生数学建模竞赛、全国大学生市场调查与分析大赛、美国大学生数学建模竞赛、全国研究生数学建模大赛、全国大学生统计建模大赛等多项学科竞赛,获得包括国家一等奖在内的国家级奖项20余项,省部级以上奖励30余项。



四、科学研究

(1)科研成果:

主持国家自然科学基金青年项目1项,湖北省自然科学基金面上项目1项,中央高校基本科研业务费专项基金重点项目和一般项目各1项,横向课题1项;以核心科研成员身份参与国家自然科学基金重点项目1项,国家自然科学基金面上项目10余项,湖北省自然科学基金面上项目1项,北京市社会科学基金后期资助项目一般项目1项,中国无机盐工业协会2024年重点课题研究专题1项,发表科研论文50余篇,软件著作权10余部。

(2)科研项目:

1.湖北省自然科学基金面上项目,基因调控网络复杂动力学行为分析与控制,2019/01-2020/12,已结题,主持;

2.国家自然科学基金青年项目,基于多尺度耦合特征的基因调控网络动态演化机制研究,2016/01-2018/12,已结题,主持;

3.中央高校基本科研业务费专项基金重点项目,大数据环境下基因调控网络重构及演化分析,已结题,主持;

4.国家自然科学基金重点项目,混杂非线性系统的性能分析与控制设计及应用,2017/01-2021/12,已结题,参与;

5.中国无机盐工业协会2024年重点课题研究专题,全球锂资源供需格局分析和我国锂资源产业链供应链韧性研究,2024/10-2025/02已结题,参与;

6.北京市社会科学基金后期资助项目一般项目,国家能源和矿产资源需求预测的数据分析--以印度为例,2026/01-2027/12,在研,参与。

(3)学术论文:

[1]  Zonglin Yang, Guang Ling*, Zhi-Hong Guan, Yuan Ge, Ming-Feng Ge. Finite-Time Adaptive Fuzzy Control for Strict Feedback Systems with Asymmetric State Constraints and Prescribed Performance. Journal of the Franklin Institute, 2025, 362(16): 108076.

[2]  Wenqiu Pan, Guang Ling*, Feng Liu. mGNN-bw: Multi-Scale Graph Neural Network Based on Biased Random Walk Path Aggregation for ASD Diagnosis[J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2025, 33: 900-910.

[3]Peng Wang, Guang Ling*, Pei Zhao, Zhi-Hong Guan, Ming-Feng Ge. Dynamically identify important nodes in the hypergraph based on the ripple diffusion and ant colony collaboration model. Journal of Network and Computer Applications. 2025, 236(2): 104107.

[4]Xiao Xu, Guang Ling*, Fang Wang, Lianyu Cheng, Ming-Feng Ge. Grey dispersion entropy based on truncated Gaussian whitenization function: a novel time series complexity measure. Nonlinear Dynamics. 2025, 113: 8305–8327.

[5]Peng Wang, Guang Ling*, Pei Zhao, Wenqiu Pan, Ming-Feng Ge. Identification of important nodes in multi-layer hypergraphs based on fuzzy gravity model and node centrality distribution characteristics. Chaos Solitons & Fractals, 2024, 188: 115503.

[6]Lianyu Cheng, Guang Ling*, Feng Liu, Ming-Feng Ge. Application of uniform experimental design theory to multi-strategy improved sparrow search algorithm for UAV path planning. Expert Systems with Applications, 2024, 255(7):124849.

[7]Pei Zhao, Guang Ling*, Xiangxiang Song. ELFNet: An Effective Electricity Load Forecasting Model Based on a Deep Convolutional Neural Network with a Double-Attention Mechanism. Applied Sciences, 2024, 14(14): 6270.

[8]Zonglin Yang, Guang Ling*, Ming-Feng Ge. Secure impulsive tracking of multi-agent systems with directed hypergraph topologies against hybrid deception attacks. Neural Networks, 2024, 180(9): 106691.

[9]Xiangxiang Song, Guang Ling*, Wenhui Tu and Yu Chen. Knowledge-guided heterogeneous graph convolutional network for aspect-based sentiment analysis. Electronics, 2024, 13(517): 13030517.

[10]  Bozhi Yao, Guang Ling*, Feng Liu, Ming-Feng Ge. Multi-source variational mode transfer learning for enhanced PM2.5 concentration forecasting at data-limited monitoring stations. Expert Systems with Applications, 2024, 238: 121714.

[11]Yu Chen, Guang Ling*, Xiangxiang Song, Wenhui Tu. Characterizing the statistical complexity of nonlinear time series via ordinal pattern transition networks. Physica A, 2023, 618: 128670.

[12]Yu-Han Tong, Guang Ling*, Zhi-Hong Guan, Qingju Fan, Li Wan. Refined Composite Multiscale Phase Rényi Dispersion Entropy for Complexity Measure. International Journal of Bifurcation and Chaos, 2023, 33(05): 2350054.

[13]Wenhui Tu, Guang Ling*, Feng Liu, Fuyan Hu, Xiangxiang Song. GCSTI: A Single-Cell Pseudotemporal Trajectory Inference Method Based on Graph Compression. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2023, 20(5): 2945 – 2958.

[14]Li Wan, Guang Ling*, Zhi-Hong Guan, Qingju Fan, Yu-HanTong. Fractional multiscale phase permutation entropy for quantifying the complexity of nonlinear time series. Physica A, 2022, 600, 127506. 

[15]Guang Ling*, Xinzhi Liu, Zhi-Hong Guan, Ming-Feng Ge, Yu-Han Tong. Input-to-State Stability for Switched Stochastic Nonlinear Systems with Mode-dependent Random Impulses, Information Sciences, 2022, 596, 588-607.

[16]Jingjing Xia, Guang Ling*, Qingju Fan, Fang Wang, Ming-Feng Ge. Evidential link prediction method based on the importance of high-order path index. Modern Physics Letters B, 35(33), 2021, 2150487.

[17]Rongrong Song, Guang Ling*, Qingju Fan, Ming-Feng Ge, Fang Wang. Link prediction based on heterogeneous degree penalization with extending neighbors and clustering coefficient. International Journal of Modern Physics C, 2022, 33(3): 2250033.

[18]Guang Ling*, Ming-Feng Ge, Xinghua Liu, Gaoxi Xiao,Qingju Fan. Stochastic quasi-synchronization of heterogeneous delayed impulsive dynamical networks via single impulsive control. Neural Networks, 2021, 139, 223-236.

[19]Guang Ling, Ming-Feng Ge, Yu-Han Tong, Qingju Fan. Exponential Synchronization of Delayed Switching Genetic Oscillator Networks via Mode-Dependent Partial Impulsive Control, Neural Processing Letters, 2021, 53(2): 1845-1863.

[20]Guang Ling, Xinzhi Liu*, Ming-Feng Ge, YonghongWu. Delay-dependent cluster synchronization of time-varying complex dynamical networks with noise via delayed pinning impulsive control, Journal of the Franklin Institute, 2021, 358(6): 3193-3214. 

(4)学术兼职:

中国现场统计研究会多元分析应用专业委员会理事;中国现场统计研究会经济与金融统计分会理事;全国工业统计学教学研究会数字经济与区块链技术协会理事;全国工业统计学教学研究会数字经济与区块链技术协会理事;中国现场统计研究会贝叶斯统计分会理事;IEEE(美国电气与电子工程师协会)会员。