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高忠科

Date:2024年03月22日

个人资料:

姓名高忠科

职称教授

学科专业:检测技术与bet365官网装置

通讯地址:bet365官网电气与bet365官网工程学院26教学楼E

电子信箱:zhongkegao@9u15.com

 

主要经历:

(1) 2016.07-至今 bet365官网电气bet365官网与信息工程学院,教授,博士生导师;

(2) 2013.07-2016.06 bet365官网电气与bet365官网工程学院,副教授,博士生导师(2016.04)

(3) 2010.09-2013.06 bet365官网电气与bet365官网工程学院,讲师;

(4) 2007年和2010年获bet365官网工学硕士学位和博士学位;

(5) 2009年至2010年国家公派赴美国亚利桑那州立大学博士联合培养一年;

(6) 2013年作为访问教授赴德国洪堡大学合作研究,合作者Jürgen Kurths院士;

(7) 2015年作为访问教授赴香港城市大学合作研究,合作者陈关荣院士;

(8) 2016年作为访问教授赴新加坡国立大学合作研究;

(9) 2018年作为访问教授赴德国PIK研究所合作研究,合作者Jürgen Kurths院士;

(10) 2019年作为访问教授赴英国阿伯丁大学合作研究,合作者Celso Grebogi院士。

 

简介:

高忠科,1982年生,bet365官网电气bet365官网与信息工程学院教授、博士生导师,bet365官网人工智能与网络科学研究所所长,国家优秀青年科学基金获得者(国家优青),天津市杰青,天津市中青年科技创新领军人才,全球高被引科学家,中国高被引学者,IEEE Senior Member。主要研究方向为复杂网络多源信息融合理论、新型传感器技术、多相流检测、脑机融合与混合智能、智能医学、脑控康复机器人、水下机器人与自主智能系统等,已在IEEE Transactions on Industrial InformaticsIEEE Transactions on Neural Networks and Learning SystemsChemical Engineering JournalIEEE Journal of Biomedical and Health InformaticsIEEE Transactions on Instrumentation and MeasurementIEEE Transactions on Systems, Man, and Cybernetics: SystemsIEEE Transactions on Circuits and Systems IIIEEE Sensors JournalIEEE Transactions on CyberneticsJournal of Neural EngineeringNeural NetworksKnowledge-Based Systems等国际期刊上发表SCI检索论文174篇,其中第一/通讯作者SCI论文121篇,论文SCI引用4000余次,Google Scholar引用5000余次,12篇第一作者论文入选ESI高被引论文。在德国Springer出版社出版英文学术专著一部,第一发明人中国发明专利116项。主持国家自然科学基金、国家重点研发计划课题等国家级、省部级和企业合作项目20余项。获2013年全国百篇优秀博士学位论文提名奖,2018年和20192次获得英国皇家物理学会(IOP)高被引中国作者奖,2021年首届强国青年科学家提名奖(全国40人)。研究成果被来自美国、英国、德国、加拿大、意大利、瑞士、日本等十余个国家的数百位著名学者正面引用和评价,其中包括多位中国工程院院士、美国科学院院士,欧洲科学院院士,加拿大工程院院士,美国工程院院士,英国皇家工程院院士,德国国家科学院院士,澳大利亚技术科学与工程院院士和多位IEEE FellowASME Fellow

 

作为负责人承担的主要科研项目:

1. 国家自然科学基金优秀青年科学基金项目,多相流传感器信息融合理论与应用,项目编号:619220622020.01-2022.12,项目负责人。

2. 国家自然科学基金面上项目,基于复杂网络和深度学习的两相流可视化与动力学建模研究,项目编号:618731812019.01-2022.12,项目负责人。

3. 天津市杰出青年科学基金项目,复杂网络多源信息融合理论与应用,2021.10-2025.09,项目负责人。

4. 国家自然科学基金面上项目,基于复杂网络多元信息融合的油井两相流流型演化机制研究,项目编号:614732032015.01-2018.12,项目负责人。

5. 国家自然科学基金青年基金项目,水平油水两相流复杂网络非线性动力学特性研究,项目编号:611041482012.01-2014.12,项目负责人。

6. 天津市自然科学基金面上项目,基于复杂网络的两相流多源异构传感器信息融合研究,项目编号:16JCYBJC182002016.04-2019.03,项目负责人。

 

代表性论著、学术著作:

学术论文:

(1) He Wang, Peiyin Chen, Meng Zhang, Jianbo Zhang, Xinlin Sun, Mengyu Li, Xiong Yang, Zhongke Gao, EEG-Based Motor Imagery Recognition Framework via Multisubject Dynamic Transfer and Iterative Self-Training, IEEE Transactions on Neural Networks and Learning Systems, 2023, DOI: 10.1109/TNNLS.2023.3243339. (SCI, IF=14.255)

(2) Huazhen Chen, Jianpeng An, Bochang Jiang, Lili Xia, Yunhao Bai, Zhongke Gao, WS-MTST: Weakly Supervised Multi-Label Brain Tumor Segmentation With Transformers, IEEE Journal of Biomedical and Health Informatics, 2023, 27(12): 5914-5925. (SCI, IF=7.7)

(3) Lili Xia, Zhiyong Qu, Jianpeng An, Zhongke Gao, A Weakly Supervised Method With Colorization for Nuclei Segmentation Using Point Annotations, IEEE Transactions on Instrumentation and Measurement, 2023, 72: 1-11. (SCI, IF=5.6)

(4) Jianbo Zhang, Chao Ma, Peiyin Chen, Mengyu Li, Ruiqi Wang, Zhongke Gao, Co-Attention-Based Cross-Stitch Network for Parameter Prediction of Two-Phase Flow, IEEE Transactions on Instrumentation and Measurement, 2023, 72: 1-12. (SCI, IF=5.6)

(5) Chao Ma, Meng Zhang, Xinlin Sun, He Wang, Zhongke Gao, Dynamic Threshold Distribution Domain Adaptation Network: A Cross-Subject Fatigue Recognition Method Based on EEG Signals, IEEE Transactions on Cognitive and Developmental Systems, 2024, 16(1): 190-201. (SCI, IF=5)

(6) Dongmei Lv, Weidong Dang, Xinlin Sun, Zhongke Gao, EEG-Based Multi-Frequency Multilayer Network for Exploring the Brain State Evolution Underlying Motor Imagery, IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2023, 13(3): 712-719. (SCI, IF=4.6)

(7) Peiyin Chen, Zhongke Gao, Miaomiao Yin, Jialing Wu, Kai Ma, Celso Grebogi, Multiattention Adaptation Network for Motor Imagery Recognition, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, 52(8): 5127-5139. (SCI, IF=11.471)

(8) Zhongke Gao, Linhua Hou, Weidong Dang, Xinmin Wang, Xiaolin Hong, Xiong Yang, Guanrong Chen, Multitask-based temporal-channel wise CNN for parameter prediction of two-phase flows, IEEE Transactions on Industrial Informatics, 2021, 17(9):6329-6336. (SCI, IF=11.648)

(9) Zhongke Gao, Weidong Dang, Mingxu Liu, Wei Guo, Kai Ma, Guanrong Chen, Classification of EEG signals on VEP-based BCI systems with broad learning, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021, 51(11): 7143-7151. (SCI, IF=11.471)

(10) Zhongke Gao, Mingxu Liu, Weidong Dang, Chao Ma, Linhua Hou, Xiaolin Hong, Multilayer Limited Penetrable Visibility Graph for Characterizing the Gas-Liquid Flow Behavior, Chemical Engineering Journal, 2021, 407:127229. (SCI, IF=16.744)

(11) Yuxuan Yang, Zhongke Gao, Yanli Li, Qing Cai, Norbert Marwan, Juergen Kurths, A complex network-based broad learning system for detecting driver fatigue from EEG signals, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021, 51(9):5800-5808. (SCI, IF=11.471)

(12) Zhongke Gao, Yanli Li, Yuxuan Yang, Na Dong, Xiong Yang, and Celso Grebogi, A coincidence filtering-based approach for CNNs in EEG-based recognition, IEEE Transactions on Industrial Informatics, 2020, 16(11):7159-7167. (SCI, IF=11.648)

(13) Zhongke Gao, Xinming Wang, Yuxuan Yang, Chaoxu Mu, Qing Cai, Weidong Dang, Siyang Zuo, EEG-based spatio-temporal convolutional neural network for driver fatigue evaluation, IEEE Transactions on Neural Networks and Learning Systems, 2019, 30(9): 2755-2763. (SCI, IF= 14.255)

(14) Weidong Dang, Zhongke Gao, Linhua Hou, Dongmei Lv, Shuming Qiu, and Guanrong Chen, A novel deep learning framework for industrial multiphase flow characterization, IEEE Transactions on Industrial Informatics, 2019,15(11): 5954-5962. (SCI, IF=11.648)

(15) Zhongke Gao, Weidong Dang, Chaoxu Mu, Yuxuan Yang, Shan Li, Celso Grebogi, A novel multiplex network-based sensor information fusion model and its application to industrial multiphase flow system, IEEE Transactions on Industrial Informatics, 2018, 14(9): 3982-3988. (SCI, IF=11.648)

(16) Zhongke Gao, Xinlin Sun, Mingxu Liu, Weidong Dang, Chao Ma, Guanrong Chen, Attention-based Parallel Multiscale Convolutional Neural Network for Visual Evoked Potentials EEG Classification, IEEE Journal of Biomedical and Health Informatics, 2021, 25(8):2887-2894. (SCI, IF= 7.021)

(17) Weidong Dang, Zhongke Gao, Dongmei Lv, Xinlin Sun, Chichao Cheng, Rhythm-dependent multilayer brain network for the detection of driving fatigue, IEEE Journal of Biomedical and Health Informatics, 2021, 25(3): 693-700. (SCI, IF=7.021)

(18) Weixin Niu, Chao Ma, Xinlin Sun, Mengyu Li, Zhongke Gao, A Brain Network Analysis-Based Double Way Deep Neural Network for Emotion Recognition, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023, 31: 917-925. (SCI, IF=4.528)

(19) Biao Sun, Beida Song, Jiajun Lv, Peiyin Chen, Xinlin Sun, Chao Ma, Zhongke Gao, A Multi-Scale Feature Extraction Network Based on Channel-Spatial Attention for Electromyographic Signal Classification, IEEE Transactions on Cognitive and Developmental Systems, 2023, DOI: 10.1109/TCDS.2022.3167042. (SCI, IF=4.546)

(20) Xiong Yang, Yingjiang Zhou, Zhongke Gao, Reinforcement learning for robust stabilization of nonlinear systems with asymmetric saturating actuators, Neural Networks, 2023, 158:132-141. (SCI, IF=9.657)

(21) Xinlin Sun, Chao Ma, Peiyin Chen, Mengyu Li, He Wang, Weidong Dang, Chaoxu Mu, Zhongke Gao, A Novel Complex Network-Based Graph Convolutional Network in Major Depressive Disorder Detection, IEEE Transactions on Instrumentation and Measurement, 2022, 71:1-8. (SCI, IF=5.332)

(22) Peiyin Chen, He Wang, Xinlin Sun, Haoyu Li, Celso Grebogi, Zhongke Gao, Transfer Learning With Optimal Transportation and Frequency Mixup for EEG-Based Motor Imagery Recognition, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2022, 30:2866-2875. (SCI, IF=4.528)

(23) Zhongke Gao, Yangyang Wang, Xinlin Sun, Peiyin Chen, Chao Ma, A Multifeatured Time–Frequency Neural Network System for Classifying sEMG, IEEE Transactions on Circuits and Systems II: Express Briefs, 2022, 69(11):4588-4592. (SCI, IF=3.691)

(24) Mengyu Li, Chao Ma, Weidong Dang, Ruiqi Wang, Yong Liu, Zhongke Gao, DSCNN: Dilated Shuffle CNN Model for SSVEP Signal Classification, IEEE Sensors Journal, 2022, 22(12):12036–12043. (SCI, IF=4.325)

(25) Xiong Yang, Zhigang Zeng, Zhongke Gao, Decentralized Neurocontroller Design With Critic Learning for Nonlinear-Interconnected Systems, IEEE Transactions on Cybernetics, 2022, 52(11): 11672-11685. (SCI, IF= 19.118)

(26) Weidong Dang, Mengyu Li, Dongmei Lv, Xinlin Sun, Zhongke Gao, MHLCNN: Multi-harmonic linkage CNN model for SSVEP and SSMVEP signal classification, IEEE Transactions on Circuits and Systems II: Express Briefs, 2022, 69(1): 244-248. (SCI, IF=3.691)

(27) Zhongke Gao, Zhiyong Qu, Qing Cai, Linhua Hou, Mingxu Liu, Tao Yuan, A Deep Branch-Aggregation Network for Recognition of Gas-Liquid Two-Phase Flow Structure, IEEE Transactions on Instrumentation and Measurement, 2021, 70:5000408. (SCI, IF=5.332)

(28) Zhongke Gao, Rumei Li, Chao Ma, Linge Rui, Xinlin Sun, Core-Brain-Network-Based Multilayer Convolutional Neural Network for Emotion Recognition, IEEE Transactions on Instrumentation and Measurement, 2021, 70:2510209. (SCI, IF= 5.332)

(29) Xiaolin Hong, Qingqing Zheng, Luyan Liu, Peiyin Chen, Kai Ma, Zhongke Gao, Yefeng Zheng, Dynamic Joint Domain Adaptation Network for Motor Imagery Classification, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2021, 29:556-565. (SCI, IF=4.528)

(30) Weidong Dang, Dongmei Lv, Linge Rui, Ziang Liu, Guanrong Chen, Zhongke Gao, Studying Multi-Frequency Multilayer Brain Network via Deep Learning for EEG-Based Epilepsy Detection, IEEE Sensors Journal, 2021, 21(24): 27651-27658. (SCI, IF=4.325)

(31) Zhongke Gao, Mengyu Li, Linhua Hou, Hao Deng, Wenda Xu, Weidong Dang, Guoliang Deng, Stage-wise Densely Connected Network for Parameter Measurement of Two-phase Flows, IEEE Sensors Journal, 2021, 21(16):18123-18131. (SCI, IF=4.325)

(32) Qing Cai, Zhongke Gao, Jianpeng An, Shuang Gao, Celso Grebogi, A Graph-Temporal fused dual-input Convolutional Neural Network for Detecting Sleep Stages from EEG Signals, IEEE Transactions on Circuits and Systems II: Express Briefs, 2021, 68(2): 777-781. (SCI, IF=3.691)

(33) Zhongke Gao, Zhu Gong, Qing Cai, Chao Ma, Celso Grebogi, Complex Network Analysis of Experimental EEG Signals for Decoding Brain Cognitive State, IEEE Transactions on Circuits and Systems II: Express Briefs, 2021, 68(1): 531-535. (SCI, IF=3.691)

(34) Zhongke Gao, Xinmin Wang, Yuxuan Yang, Yanli Li, Kai Ma, Guanrong Chen, A channel-fused dense convolutional network for EEG-based emotion recognition, IEEE Transactions on Cognitive and Developmental Systems, 2021, 13(4): 945-954. (SCI, IF=4.546)

(35) Zhongke Gao, Zhiyong Qu, Hongtao Wang, Chao Ma, Characterization of Two-Phase Flow Structure by Deep Learning-Based Super Resolution, IEEE Transactions on Circuits and Systems II: Express Briefs, 2021, 68(2): 782-786. (SCI, IF=3.691)

(36) Jianpeng An, Qing Cai, Zhiyong Qu, Zhongke Gao, COVID-19 Screening in Chest X-Ray Images Using Lung Region Priors, IEEE Journal of Biomedical and Health Informatics, 2021, 25(11): 4119-4127. (SCI, IF=7.021)

(37) He Wang, Xinshan Zhu, Pinyin Chen, Yuxuan Yang, Chao Ma, Zhongke Gao, A gradient-based automatic optimization CNN framework for EEG state recognition, Journal of Neural Engineering, 2021, 19(1):016009. (SCI, IF=5.043)

(38) Yuxuan Yang, Zhongke Gao, Yanli Li, He Wang, A CNN identified by reinforcement learning-based optimization framework for EEG-based state evaluation, Journal of Neural Engineering, 2021, 18(4): 1741-2552. (SCI, IF= 5.043)

(39) Zhongke Gao, Weidong Dang, Xinmin Wang, Xiaolin Hong, Linhua Hou, Kai Ma, Matjaz Perc, Complex networks and deep learning for EEG signal analysis, Cognitive Neurodynamics, 2021, 15(3):69-388 (SCI, IF=3.473)

(40) Zhongke Gao, Hongtao Wang, Weidong Dang, Yongqiang Li, Xiaolin Hong, Mingxu Liu, Guanrong Chen, Complex network analysis of wire-mesh sensor measurements for characterizing vertical gas-liquid two-phase flows, IEEE Transactions on Circuits and Systems II: Express Briefs, 2020, 67(6): 1134-1138. (SCI, IF= 3.691)

(41) Zhongke Gao, Xiaolin Hong, Weidong Dang, Linhua Hou, and Mingxu Liu, Multiresolution multiplex network for analyzing multichannel fluid flow signals, IEEE Transactions on Circuits and Systems II: Express Briefs, 2020, 67(10):2179-2183. (SCI, IF= 3.691)

(42) Zhongke Gao, Tao Yuan, Xinjun Zhou, Chao Ma, Kai Ma, Pan Hui, A Deep Learning Method for Improving the Classification Accuracy of SSMVEP-based BCI, IEEE Transactions on Circuits and Systems II: Express Briefs, 2020, 67 (12):3447-3451. (SCI, IF= 3.691)

(43) Runfeng Zhang, Shaoqiong Yang, Yanhui Wang, Shuxin Wang, Zhongke Gao, Chenyi Luo, Three-dimensional regional oceanic element field reconstruction with multiple underwater gliders in the Northern South China Sea, Applied Ocean Research, 2020, 105: 102405 (SCI, IF=3.761)

(44) Zhongke Gao, Ming-Xu Liu, Wei-Dong Dang, Qing Cai, A novel complex network-based deep learning method for characterizing gas-liquid two-phase flow, Petroleum Science (石油科学英文版) 2020, 18(1):259-268. (SCI, IF=4.757,中国科技期刊卓越行动计划-领军期刊)

(45) Chaoxu Mu, Yong Zhang, Zhongke Gao, Changyin Sun, ADP-based robust tracking control for a class of nonlinear systems with unmatched uncertainties, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2020, 50 (11):4056-4067. (SCI, IF=11.471)

(46) Na Dong, Jianfang Chang, Aiguo Wu, Zhongke Gao, A novel convolutional neural network framework based solar irradiance prediction method, International Journal of Electrical Power & Energy Systems, 2020, 114: 105411. (SCI, IF=5.659)

(47) Xiong Yang, Zhongke Gao, Jinhui Zhang, Event-driven H control with critic learning for nonlinear systems, Neural Networks, 2020, 132:30-42. (SCI, IF=9.657)

(48) Zhongke Gao, Dongmei Lv, Weidong Dang, Mingxu Liu, Xiaolin Hong, Multilayer network from multiple entropies for characterizing gas-liquid nonlinear flow behavior, International Journal of Bifurcation and Chaos, 2020, 30(1):2050014. (SCI, IF=2.450)

(49) Weidong Dang, Zhongke Gao, Xinlin Sun, Rumei, Li, Qing Cai, Celso Grebogi, Multilayer brain network combined with deep convolutional neural network for detecting major depressive disorder, Nonlinear Dynamics, 2020, 102(2):667-677 (SCI, IF=5.741)

(50) Zhongke Gao, Shan Li, Qing Cai, Weidong Dang, Yuxuan Yang, Chaoxu Mu, Pan Hui, Relative wavelet entropy complex network for improving EEG-based fatigue driving classification, IEEE Transactions on Instrumentation and Measurement, 2019, 68(7): 2491-2497. (SCI, IF= 5.332)

(51) Qing Cai, Zhongke Gao, Yuxuan Yang, Weidong Dang, Celso Grebogi, Multiplex limited penetrable horizontal visibility graph from EEG signals for driver fatigue detection, International Journal of Neural Systems, 2019, 29(5):1850057. (SCI, IF=6.325)

(52) Yanhui Wang, Xinrui Shen, Shaoqiong Yang, Zhongke Gao, Three-dimensional dynamic analysis of observed mesoscale eddy in the South China Sea based on complex network theory, Europhysics Letters, 2019, 128:60005 (IF=1.947)

(53) Chaoxu Mu, Qian Zhao, Zhongke Gao, Changyin Sun, Q-learning solution for optimal consensus control of discrete-time multiagent systems using reinforcement learning, Journal of the Franklin Institute, 2019, 356(13):6946-6967. (SCI, IF=4.246)

(54) Zhongke Gao, Kaili Zhang, Weidong Dang, Yuxuan Yang, Zibo Wang, Haibin Duan, Guanrong Chen, An adaptive optimal-Kernel time-frequency representation-based complex network method for characterizing fatigued behavior using the SSVEP-based BCI system, Knowledge-Based Systems, 2018, 152: 163-171. (SCI, IF=8.139)

(55) Zhongke Gao, Shan Li, Wei-Dong Dang, Yu-Xuan Yang, Younghae Do, Celso Grebogi, Wavelet Multiresolution Complex Network for Analyzing Multivariate Nonlinear Time Series, International Journal of Bifurcation and Chaos, 2017, 27(8): 1750123. (SCI, IF=2.450)

(56) Zhongke Gao, Qing Cai, Yu-Xuan Yang, Na Dong, Shan-Shan Zhang, Visibility graph from adaptive optimal kernel time-frequency representation for classification of epileptiform EEG, International Journal of Neural Systems, 2017, 27(4):1750005. (SCI, IF=6.325)

(57) Zhongke Gao, Shanshan Zhang, Weidong Dang, Shan Li, Qing Cai, Multilayer network from multivariate time series for characterizing nonlinear flow behavior, International Journal of Bifurcation and Chaos, 2017, 27(4): 1750059 (SCI, IF=2.450)

(58) Zhongke Gao, Yuxuan Yang, Lusheng Zhai, Ningde Jin, Guanrong Chen, A four-sector conductance method for measuring and characterizing low-velocity oil-water two-phase flows, IEEE Transactions on Instrumentation and Measurement, 2016, 65(7): 1690-1697. (SCI, IF=5.332)

(59) Zhongke Gao, Michael Small, Jürgen Kurths, Complex network analysis of time series, Europhysics Letters, 2016, 116:50001 (IF=1.947)

(60) Zhongke Gao, Yuxuan Yang, Lusheng Zhai, Meishuang Ding, Ningde Jin, Characterizing slug to churn flow transition by using multivariate pseudo Wigner distribution and multivariate multiscale entropy, Chemical Engineering Journal, 2016, 291:74-81. (SCI, IF=16.744)

学术专著:

(1) Zhong-Ke Gao, Ning-De Jin, Wen-Xu Wang,Nonlinear Analysis of Gas-Water/ Oil-water Two-Phase Flow in Complex Networks, Springer, Berlin, Germany, 2014, ISBN: 978-3-642-38372-4.

 

国家发明专利:

(1) 一种用于两相流检测的四扇区分布式电导传感器, 发明专利, 第一发明人, 专利号:2014100333387(已授权)

(2) 一种分布式电导传感器的结构参数优化方法, 发明专利, 第一发明人, 专利号:2014100333372(已授权)

(3) 一种基于分布式电导传感器的两相流测量系统, 发明专利, 第一发明人, 专利号:2014100339415(已授权)

(4) 基于模态迁移复杂网络的气液相含率测量及验证方法, 发明专利, 第一发明人, 专利号:2014102291181(已授权)

(5) 基于频率复杂网络的垂直油水相含率测量及验证方法, 发明专利, 第一发明人, 专利号:2014102287186(已授权)

(6) 基于多元相空间复杂网络的油水相含率测量及验证方法, 发明专利, 第一发明人, 专利号:2014102287190(已授权)

(7) 基于多层复杂网络的两相流多元复阻抗检测信息融合方法, 发明专利, 第一发明人, 专利号:2016108891696(已授权)

(8) 基于复杂网络的深度学习模型及在测量信号分析中的应用, 发明专利, 第一发明人, 专利号:2016108881247(已授权)

(9) 基于网格传感器的两相流空间复杂网络可视化分析方法, 发明专利, 第一发明人, 专利号:2016108876817(已授权)

(10) 基于递归图的深度学习模型及在油水相含率测量中的应用, 发明专利, 第一发明人, 专利号:2016108884902(已授权)

(11) 基于多尺度加权递归网络的两相流网络可视化方法及应用, 发明专利, 第一发明人, 专利号:2016108891709(已授权)

(12) 基于复杂网络和深度学习的两相流多元信息融合法及应用, 发明专利, 第一发明人, 专利号:2016108893579(已授权)

(13) 基于小波多分辨率双层复杂网络的多源信息融合法及应用, 发明专利, 第一发明人, 专利号:2016108886166(已授权)

(14) 用于脑状态监测的头戴式智能穿戴电极数量优化法及应用, 发明专利, 第一发明人, 专利号:2016108876840(已授权)

(15) 基于多尺度网络的深度学习模型及在脑状态监测中的应用, 发明专利, 第一发明人, 专利号:2016108876836(已授权)

(16) 基于复杂网络的脑电信号分析方法及应用, 发明专利, 第一发明人, 专利号:2016108891681(已授权)

(17) 基于最优核时频分布可视图的癫痫脑电信号识别方法, 发明专利, 第一发明人, 专利号:2016108876821(已授权)

(18) 基于复杂网络的心电信号分析方法及在智能穿戴上的应用, 发明专利, 第一发明人, 专利号:2016108886170(已授权)

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(21) 基于压缩感知的P300脑机接口在智能家居中的应用方法, 发明专利, 第一发明人, 专利号:2018101693087(已授权)

(22) 融合可视图与深度学习的运动想象意念控制方法及应用, 发明专利, 第一发明人, 专利号:2018101693068(已授权)

(23) 融合递归图与深度学习的多目标SSVEP意念控制法及应用, 发明专利, 第一发明人, 专利号:2018101693034(已授权)

(24) 基于模态迁移复杂网络的机器人智能意念控制方法, 发明专利, 第一发明人, 专利号:2018101682275(已授权)

(25) 基于小波多分辨率复杂网络的脑电极优化方法及其应用, 发明专利, 第一发明人, 专利号:2018101674917(已授权)

(26) 一种饮食管理系统及其构建方法、一种食材管理方法, 发明专利, 第一发明人, 专利号:2018104322549(已授权)

(27) 基于MEMD的深度学习模型构建方法及在运动想象中的应用, 发明专利, 第一发明人, 专利号:2018101682415(已授权)

(28) 基于新型迁移学习模型的脑-肌电智能全肢体康复方法, 发明专利, 第一发明人, 专利号:2020103694274(已授权)

(29) 一种纯意念控制康复机器人的训练与模式切换方法, 发明专利, 第一发明人, 专利号:2020103669234(已授权)

(30) 基于脑肌电信号深度学习融合的脑卒中运动康复方法, 发明专利, 第一发明人, 专利号:2020103647362(已授权)

(31) 基于蒸馏学习和深度学习纯意念控制智能康复方法及应用, 发明专利, 第一发明人, 专利号:2020103668918(已授权)

(32) 基于深度学习的含水率测量方法及其在油井开采中的应用, 发明专利, 第一发明人, 专利号:2020104814786(已授权)

(33) 基于便携式脑电采集设备的脑控智能自动拍照系统及方法, 发明专利, 第一发明人, 专利号:2020104814818(已授权)

(34) 基于深度学习的胃肠道间质瘤中核分裂象智能检测方法, 发明专利, 第一发明人, 专利号:2020106243144(已授权)

(35) 基于深度学习和脑机接口的情绪识别系统及应用, 发明专利, 第一发明人, 专利号:2020104814771(已授权)

(36) 基于便携式脑电采集设备的癫痫发作预警系统及应用, 发明专利, 第一发明人, 专利号:2020104814748(已授权)

(37) 基于脑机接口和深度学习的重度抑郁症辨识系统及应用, 发明专利, 第一发明人, 专利号:2020104814767(已授权)

(38) 基于双输入卷积神经网络的睡眠阶段分类方法及应用, 发明专利, 第一发明人, 专利号:2019106375278(已授权)

(39) 基于脑机交互与深度学习的脑卒中主动式手部康复系统, 发明专利, 第一发明人, 专利号:2020104814837(已授权)

(40) 用于移动端的胃肠道间质瘤中核分裂象深度学习检测系统, 发明专利, 第一发明人, 专利号:2020106243159(已授权)

(41) 基于多尺度深度学习的病理图像病灶区域检测方法, 发明专利, 第一发明人, 专利号:2020106225377(已授权)

(42) 基于迁移学习的胃肠道间质瘤中核分裂象检测系统, 发明专利, 第一发明人, 专利号:2020106243267(已授权)

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软件著作:

(1) 人机交互的脑卒中康复训练系统软件V1.02021SR1081727

(2) 基于脑机接口的卒中康复系统信号辨识软件V1.02021SR1086657

(3) 病理图像检测工具软件1.02021SR0720224

(4) 病理图像标注工具软件1.02021SR0720225

 

主要学术成就、奖励及荣誉:

(1) 2019年国家优青

(2) 2021年天津市杰青

(3) 2020年天津市创新人才推进计划中青年科技创新领军人才

(4) 2019年全球高被引科学家

(5) 2021年首届强国青年科学家提名奖

(6) 2021年中国高被引学者

(7) 2019年英国皇家物理学会(IOP)高被引中国作者奖

(8) 2018年英国皇家物理学会(IOP)高被引中国作者奖

(9) 2017年入选天津市创新人才推进计划青年科技优秀人才

(10) 2013年全国百篇优秀博士学位论文提名奖

 

其他(社会兼职等):

(1) IEEE Senior Member

(2) 中国bet365官网学会高级会员

(3) 国家核电核岛装备产业计量测试联盟副理事长

(4) 中国指挥与控制学会网络科学与工程专委会委员

(5) 中国工业与应用数学学会复杂网络与复杂系统专委会委员

(6) 中国bet365官网学会能源互联网专委会委员

(7) 中国bet365官网学会环境感知与保护bet365官网专委会委员

(8) 天津市系统科学与工业控制学会副理事长

 

bet365官网人工智能与网络科学研究所主页:http://ains.9u15.com/

 

招生/招聘信息:

课题组研究方向主要包括智能脑机接口与人机混合智能、人工智能技术与应用、新型传感器技术与智能感知、水下机器人与自主智能系统、智能医学等,在复杂网络建模、新型深度学习架构设计等方面有着深厚的积累。课题组毕业去向包括腾讯、阿里、中国银行、航天科工集团等以及部分国内985高校。课题组成员可前往国际院士团队进行访学和交流。

课题组每年计划招收全日制硕士生4-6人,博士生2-3人。要求具有良好的沟通能力和团队协作精神,有解决问题的较强意愿和意识,数学、编程和英语成绩优秀者可优先考虑。