个人主页：
https://est.tongji.edu.cn/ShowPeople.aspx?info_lb=395&flag=119&info_id=1159
教育经历：
2006年3月毕业于bat365官网登录计算机系获博士学位，师从我国神经计算和信号处理领域专家曹立明教授，进行了多年的智能信号分析与算法、脑认知理论与方法研究。
研究领域：
机器学习、神经网络计算、智能算法设计、信号分析与处理、脑认知理论与方法，目前在bat365官网登录“嵌入式系统985二期平台”下设的脑认知与数字影像实验室从事脑成像信号处理的相关研究工作。
作为课程负责人，主讲的《电工学》课程2018年被评为国家精品在线开放课程。
主持科研项目：
嵌入式系统与服务计算教育部重点实验室开放课题：基于事件相关电位分析的“黄灯加速”现象研究
参与科研项目：
[1] 国家自然科学基金：面向位置服务的动态阻滞网络流模型及算法研究
[2] 国家自然科学基金：分布式计算环境下基于进化论的认知模型及其应用研究
指导创新课题：
上海市级董事长创新计划：基于脑电信号分析的小车运行多维度控制，2016.
代表性论著：
[1] Gu Rong, Yang Yusi, Cai Zhuohao. Research on cross-sensory information enhancement effect based on the analysis of multi-mode brain imaging. Photonics & Electromagnetics Research Symposium, 17-20 December 2019: 2114-2119.
[2] Gu Rong, Zhang Jie, Wang Shicong, Tong Meisong. The impact analysis of disturbance stimulation on sustained attention based on EEG. Progress in Electromagnetic Research Symposium, 8-11 August 2016: 3676-3680.
[3] Gu Rong, Zhang Jie, Zhou Junhe, Tong Meisong. The Baroque music’s influence on learning efficiency based on the research of eye movement. IEEE International Conference on Teaching, Assessment and Learning for Engineering, Wellington, New Zealand, 8-10 December 2014: 511-515.
[4] Gu Rong, Zhang Jie, Zhou Junhe, Tong Meisong. The Baroque music’s influence on learning efficiency based on the research of brain cognition. Progress in Electromagnetics Research Symposium, 25-28 August 2014: 1527-1531.
[5] Gu Rong, Wang Jingjing, Li Jie. The influence of the Baroque music on learning efficiency from the perspective of EEG analysis. Proceedings of the First International Symposium on Pedagogical research, 14-15 November 2013.
[6] Gu Rong, Li Jie. Study on the optimum state for classroom learning from brain cognition perspective - Research on relaxed alertness. Journal of Convergence Information Technology, 2012, 7(23): 564-571.
[7] Gu Rong, Zhang Hongyun, The Application of improved immunogenetic algorithm in signal timing. International Joint Conference on Bioinformatics. Systems Biology and Intelligent Computing, 3-5 August 2009: 612-615.
[8] 顾榕, 童美松. 电工学原理. 电子工业出版社, 2014.
