姓名：秦迎梅 职称：讲师

一．研究方向：神经控制工程（数据分析、网络建模与控制）

二．个人荣誉：

Ø“131”创新型人才培养工程第二层次人选
Ø2015年全国大学生“西门子杯”工业自动化挑战赛（ITEM1）设计开发型赛项一等奖

三．近期承担科研项目：

1. 国家自然科学基金青年科学基金项目：基于皮层可塑性的创伤后癫痫发作机理和电场调控研究（**，25万），2015.01-2017.12，在研，主持
2. 天津市应用基础与前沿技术研究计划（自然科学基金）青年项目：癫痫神经元网络建模及外电场闭环控制研究（17JCQNJC03700，6万），2017.04-2020.03，在研，主持
3. 天津市应用基础与前沿技术研究计划（自然科学基金）一般项目：癫痫神经元网络建模及外电场闭环控制研究（15JCYBJC19000，10万），2015.04-2018.03，在研，参与，第3
4. 国家自然科学基金青年科学基金项目：基于逆行调控皮层振荡的深部脑刺激作用机理研究（**，24.6万），2016.01-2018.12，在研，参与，第3
5. 国家自然科学基金青年科学基金项目：阿尔茨海默症的突触损毁与补偿机制研究（**，22万）2017.01-2019.12，在研，参与，第4
6. 校级科研启动项目：外电场对创伤后癫痫调控机制的研究（KYQD14006，2万），2014.04-2016.03，在研，主持
7. 天津市应用基础与前沿技术研究计划青年基金项目:基于前馈网络的癫痫放电传播机理研究（No.13JCQNJC03700， 6万），2013.04-2016.03，已结题，参与，第8
8. 国家自然科学基金青年科学基金项目：基于混合模式振荡理论的神经元外电场作用的量化机制研究（**，20万），2010.01-2012.12，已结题，参与，第6

四. 近期发表论文：

[1] Ying-MeiQin,Cong Men, Jia Zhao, Chun-Xiao Han and Yan-QiuChe. Toward heterogeneity infeedforward network with synaptic delays based on FitzHugh-Nagumo model.InternationalJournal of Modern Physics B. 2018 , 32(1) : **.
[2] Ying-MeiQin,Jiang Wang, Cong Men, Bin Deng, Xi-Le Wei, Hai-Tao Yu,Wai-Lok Chan. Stochasticresonance in feedforward acupuncture networks. Commun NonlinearSciNumerSimulat. 2014, 19(10) : 3660–3670. (SCI，二区)
[3] YangLiu, Jiang Wang, LihuiCai, Yingyuan Chen, Yingmei Qin2*.Epilepticseizure detection from EEG signals with phase-amplitude cross-frequencycoupling and Support Vector Machine. International Journal of Modern Physics B.Vol. 2018 32 (8): **
[4] QiChen, Jiang Wang , Shuangming Yang, Yingmei Qin, Bin Deng, Xile Wei, Areal-time FPGA implementation of a biologically inspired central patterngenerator network.Neurocomputing , 2017 , 244 (C) :63-80.
[5] JiaZhao, Bin Deng,Yingmei Qin, Cong Men, Jiang Wang, Xile Wei, JianbingSun. Weak electric fields detectability in a noisy neural network.CognNeurodyn.(2017) 11(1): 81-90.
[6] HanRuixue, Wang Jiang, Miao Rui，DengBin, Qin Yingmei, Yu Haitao, Wei Xile. Propagation of CollectiveTemporal Regularity in Noisy Hierarchical Networks. IEEE Transactionson Neural Networks and Learning Systems, 2017, 28（1）:191~205 ; SCIE
[7] FeiSu?, BinDeng?,Hongji Li?,Shuangming Yang?,Yingmei Qin?, Jiang Wang? and Chen Liu?,?FPGA-basedhardware simulation of nonlinear autoregressive Volterra model to reconstructthe single neuron spike pattern. Vol. 31 (2017) **.
[8] RuixueHan, Jiang Wang, Haitao Yu, Bin Deng, Xilei Wei, Yingmei Qin, and HaixuWang. Intrinsic excitability state of local neuronal population modulatessignal propagation in feed-forward neural networks.Chaos 25, 043108(2015).
[9] JiangWang*, Ruixue Han*, Xilei Wei*, Yingmei Qin?, Haitao Yu*,Bin Deng*.Weaksignal detection and propagation in diluted feed forward neural network withrecurrent excitation and inhibition. Int. J. Mod. Phys. B 30, **(2016)
[10] Ying mei Qin,Chun-Xiao Han, YanqiuChe, Huiyan Li. Efficient Epileptic Seizure DetectionBased on Electroencephalography Signal. Chinese Control Conference, 2017:5324-5327.第一标注
[11] Yingmei Qin,Bei Liu, Xiaobin Wang,Chunxiao Han &YanqiuChe. Elimination of chaos in a light-emitting diodesystem with optoelectronic feedback. Material Science and EnvironmentalEngineering(MSEE2015), 2016: 609-612.
[12] Ying-Mei Qin,Chun-Xiao Han, Bei Liu, Yan-QiuChe. Minimal Neuronal Model for the TransmissionPath of Acupuncture Signal. 2015 International Conference on Computer Scienceand Intelligent Communication (CSIC 2015).
[13] YanqiuChe, Ying mei Qin*,JiaZhao, Chun-Xiao HanFiring patterns in delayed feedforward networks with STDPrules. Chinese Control Conference , 2017 :2006-2010.
[14] Zhenxi Song,Jiang Wang, LihuiCai, Bin Deng and Yingmei Qin. Epileptic Seizure Detection ofElectroencephalogram Based on Weighted-Permutation Entropy. 2016 12th WorldCongress on Intelligent Control and Automation (WCICA),PP:2819-2823
[15] Bin Deng, HongjiLi, Fei Su, Jiang Wang, Chen Liu, and Yingmei Qin. A Nonlinear Auto-RegressiveVolterra Model Based on FPGA. 2016 12th World Congress on Intelligent Controland Automation (WCICA),PP: 962-966.
[16] Chen Jin, JiangWang, Bin Deng, Yingmei Qin and ChunxiaoHan.The Effect of Inhibitory Feedbackon Temporal Regularity in Neural Networks. A Nonlinear Auto-Regressive VolterraModel Based on FPGA. 2016 12th World Congress on Intelligent Control andAutomation (WCICA),PP: 945-949.

五．联系方式（电子邮件，联系电话）：
电子邮箱：eeymqin@tju.edu.cn
联系电话：+86 137-0206-0839