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龙飞（1973年10月），男，博士，教授。

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2014/05---今贵州大学大数据与信息工程学院，教授。
2013/09---2014/05贵州大学电子信息工程学院，教授。
2008/12---2013/09贵州大学计算机科学与信息学院，教授。
2006/10---2008/12贵州大学电子科学与信息技术学院，校聘教授。
2003/09---2006/10东南大学自动化学院攻读博士学位。
2001/09---2003/07贵州师范学院数学与计算机科学学院，讲师。
1998/09---2001/07贵州大学数学系攻读硕士学位。

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1、2012年度教育部新世纪优秀人才
2、2007年度中国科学院“西部之光”人才

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1主持项目：
[1] 国家自然科学基金： 具有奇异特性的多模型混杂系统神经网络控制研究（），2013/01－2016/12。
[2] 国家自然科学基金：切换非线性动态系统的建模、分析与控制设计研究（**），2008/01－2010/12。
[3] 教育部新世纪优秀人才支持计划项目：复杂系统的建模、分析与控制优化（NCET-12-0657），2013/01－2015/12。
[4] 教育部高等学校博士学科点专项科研基金项目：奇异混杂系统的神经网络控制研究（003），2011/01－2013/12。
[6] 中国科学院“西部之光”人才培养计划项目： 一类混杂系统的鲁棒性研究（**），2008/01－2010/12。
[7] 贵州省科学基金项目：切换动态系统的神经网络控制方法研究（**），2007/06－2009/12。
2近五年论文：
[1] Zhuhong Zhang, Shigang Yue,Min Liao,Fei Long, Danger theory based artificial immune system solving dynamic constrained single-objective optimization, Soft Computing,Vol. 18, No. 1,pp. 185-206,2014.
[2] Fei Long, Hongmei Huang, and Adan Ding, Stochastic Stabilization of Itô Stochastic Systems with Markov Jumping and Linear Fractional Uncertainty, Journal of Control Science and Engineering, Vol. 2013, Article ID: 697849, 1-14 , 2013.
[3] Fei Long, Yang Xiao, Xin Chen, Zhuhong Zhang, Disturbance attenuation for nonlinear switched descriptor systems based on neural network, Neural Computing and Applications, Vol. 23, No. 7-8,pp. 2211-2219,December 2013
[4] Yang Xiao,Fei Long,Zhigang Zeng, Adaptive backstepping neural control for switched nonlinear stochastic system with time-delay based on extreme learning machine, Lecture Notes in Computer Science, Vol. 7667, pp 713-721, 2012.
[5] Changlin Li, Fei Long, and Guohui Ren，Disturbance Attenuation for a Class of Discrete-time Switched Systems with Exponential Uncertainty, J. Korean Math. Soc. 48 (2011), No. 4, pp. 775－795.
[6] Jinxing Lin, Shumin Fei, Jie Shen, Fei Long, Exponential estimates and H-infinity control for singular Markovian jump systems with interval time-varying delay, Proceedings of The Institution of Mechanical Engineers Part I-Journal of Systems and Control Engineering, 224 (4): 437-456, 2010.
[7] Lei Yu, Shumin Fei, Fei Long, Multilayer neural networks-based direct adaptive control for switched nonlinear systems, Neurocomputing, Vol. 74, Issues 1-3, pp. 481-486, 2010
[8] Fei Long, Changlin Li and Changzheng Cui, Dynamic Output Feedback H∞ Control for a Class of Switched Linear Systems with Exponential Uncertainty, International Journal of Innovative Computing, Information and Control, Vol. 6, No. 4, pp. 1727-1736, April 2010.
[9] Changzheng Cui, Fei Long and Changlin Li, Disturbance Attenuation for Switched System with Continuous-Time and Discrete-Time Subsystems: State Feedback Case, ICIC Express Letters, Vol. 4, Issue 1, pp. 205-212, 2010.
[10] Fei Long, Changlin Li and Changzheng Cui, Robust Stabilization and Disturbance Rejection for a Class of Hybrid Linear Systems Subject to Exponential Uncertainty, Journal of Dynamic Systems, Measurement and Control, ASME Transaction, Vol. 131, Art. No. 034501, pp. 1-7, March, 2009
[11] Sheng Zhang and Fei Long, Neural Network Control for a Class of Stochastic Nonlinear Switched System Based on Backstepping, Lecture Notes in Computer Science, Vol. 5552, pp. 1023-1031, 2009.
[12] Sheng Zhang and Fei Long, Neural Networks Sliding Mode Control for a Class of Switched Nonlinear Systems, Lecture Notes in Computer Science, Vol. 5552, pp. 1032-1039, 2009.
[13] Damin Zhang, Fei Long, Shaohong Cai, The dynamic behavior of SIRS epidemic model in complex networks, ICIC Express Letters, Vol. 3, No. 3, pp. 433-438, 2009.
[14] Fei Long, Shumin Fei, Zhumu Fu, Shiyou Zheng and Wei Wei, H∞ Control and quadratic stabilization of switched linear systems with linear fractional uncertainties via output feedback, Nonlinear Analysis: Hybrid Systems, Vol.2, No.1, pp.18–27, 2008
[15] Fei Long, Shumin Fei and Shiyou Zheng, State Feedback Singular H∞ Control for Switched Linear Systems, ACTA Journal---Control and Intelligent Systems, Vol. 36, No.1, pp.17-26, 2008.
[16] Fei Long, Shumin Fei, Neural networks stabilization and disturbance attenuation for nonlinear switched impulsive systems, Neurocomputing, Vol. 71, No.7-9, pp. 1741-1747, 2008.