更新时间：2023-04-14 17:28
曾志刚，男，1971年6月生，教授。03年6月在华中科技大学获系统分析与集成博士学位。8月进入中国科学技术大学自动化系控制科学与工程博士后流动站。04年9月至12月在香港中文大学自动化与计算机辅助设计工程学系进行合作研究。05年6月至12月和06年3月至9月在香港中文大学自动化与计算机辅助设计工程学系做第二站博士后。06年12月入选教育部06年度新世纪优秀人才支持计划 07年9月获得国家自然科学基金。08年4月获得霍英东第十一届青年教师基金资助，08年9月起在华中科技大学控制科学与工程系从事教学和科研工作。
担任过二十多个国际学术会议的程序委员会委员，出版主席等。为包括IEEE Transactions on Neural Networks；IEEE Transactions on Circuits and Systems I；IEEE Transactions on Circuits and Systems –II；IEEE Transactions on Systems Man and Cybernetics - Part B；IEEE Transactions on Automatic Control；Automatica在内的二十四个国际学术刊物审稿。希望招收的研究生具有自动化、数学、计算机等相关专业背景。
自动控制原理。
（2）国家自然科学基金：一种新的基于RNN簇吸引子的模式流识别方法研究（60405002）。
（3）教育部 “新世纪优秀人才支持计划” （NCET-06-0658）“基于神经网络的模式识别和联想记忆的理论研究”。
（4）国家自然科学基金：网络簇多吸引子协调切换及多目标流异联想研究(60774051)资助。
（5）霍英东第十一届青年教师基金：“基于切换网络簇多吸引子的动态灰度流记忆研究(111068)”
（1） Zhigang Zeng, Jun Wang, “Design and analysis of high-capacity associative memories based on a class of discrete-time recurrent neural networks,”IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, Vol. 38, No. 6, pp. 1525-1536, 2008.
（2） Zhigang Zeng, Pei Yu and Xiaoxin Liao, “A new comparison method for stability theory of differential systems with time-varying delays,” International Journal of Bifurcations and Chaos, Vol.18, No. 1, pp. 169-186, 2008.
（3）Zhigang Zeng, De-Shuang Huang and Zengfu Wang, “Pattern memory analysis base on stability theory of cellular neural networks,” Applied Mathematical Modelling, Vol.32, No.1, pp.112-121, 2008.
（4）Zhigang Zeng, Jun Wang, “Analysis and design of associative memories based on recurrent neural networks with linear saturation activation functions and time-varying delays,” Neural Computation, Vol. 19, No. 8, pp. 2149-2182, 2007.
（5）Zhigang Zeng, Jun Wang, “Global exponential stability of recurrent neural networks with time- varying delays in the presence of strong external stimuli,” Neural Networks, Vol. 19, No. 10, pp. 1528-1537, 2006.
（6）Zhigang Zeng, Jun Wang, “Multiperiodicity of discrete-time delayed neural networks evoked by periodic external inputs,” IEEE Transactions on Neural Networks, (Regular Papers), Vol. 17, No.5, pp. 1141-1151，2006.
（7）Zhigang Zeng, Jun Wang, “Improved conditions for global exponential stability of recurrent neural networks with time-varying delays,” IEEE Transactions on Neural Networks, (Regular Papers), Vol. 17, No.3, pp. 623-635，2006.
（8）Zhigang Zeng, Jun Wang, “Complete stability of cellular neural networks with time-varying delays,” IEEE Transactions on Circuits and Systems-I: Regular Papers, Vol. 53, No. 4, pp. 944-955，2006.
（9）Zhigang Zeng, Jun Wang, “Multiperiodicity and exponential attractivity evoked by periodic external inputs in delayed cellular neural networks,” Neural Computation, Vol. 18, No.4, pp.848-870, 2006.
（10）Zhigang Zeng, De-Shuang Huang and Zengfu Wang, “Global stability of a general class of discrete-time recurrent neural networks,” Neural Processing Letters, Vol.22, No.1, pp.33-47, 2005.
（11）Zhigang Zeng, Jun Wang and Xiaoxin Liao, “Global asymptotic stability and global exponential stability of neural networks with unbounded time-varying delays,” IEEE Transactions on Circuits and Systems II, Express Briefs, Vol.52, No.3, pp.168-173, 2005.
（12）Zhigang Zeng, De-Shuang Huang and Zengfu Wang, “Memory pattern analysis of cellular neural network,” Physics Letters A, Vol.342, No.1-2, pp.114–128, 2005.
（13）Zhigang Zeng, Jun Wang and Xiaoxin Liao, “Stability analysis of delayed cellular neural networks described using cloning templates,” IEEE Transactions on Circuits and Systems-I: Regular Papers. Vol.51, No.11, pp.2313-2324, 2004.
（14）Zhigang Zeng, De-Shuang Huang and Zengfu Wang, “Attractability and location of equilibrium point of cellular neural networks with time-varying delays,” International Journal of Neural Systems, Vol. 14, No. 5, pp.337-345, 2004.
（15）Zhigang Zeng, Jun Wang and Xiaoxin Liao, “Global exponential stability of neural networks with time-varying delays,” IEEE Transactions on Circuits and Systems-I: Fundamental Theory and Applications, Vol.50, No.10, pp.1353-1358, 2003.
2022年1月，曾志刚主要完成的自主无人艇机集群跨域协同关键技术及应用入选2021 年度广东省科学技术奖技术发明奖拟奖项目，一等奖。