崔健，男，博士，哈尔滨工业大学（深圳）医工学院副教授。浙江省海外高层次人才、杭州市 C 类人才。浙江大学生物医学工程与仪器学院兼任教师，硕导。主要研究脑电（眼动）信号解码、心/脑磁设备研发及降噪算法、多模态数据融合、机器学习等领域。

近年来在脑机接口与人工智能领域取得重要进展，发表论 文30余篇（谷歌学术引用1109，H指数17），包括IEEE TNNLS、 ESWA、JBHI 等。授权发明专利15项。主持之江实验室自设青年 基金“脑认知启发的人工智能研究”(20w)，参与国家重大科研 仪器研制项目“基于量子隧穿效应的室温无液氦便携式脑磁装置 研制”(获批711w)等。

一、主持的部分科研项目

[1] 国家自然科学基金委员会, 国家重大科研仪器研制项目, 62327805, 基于量子隧穿效 应的室温无液氦便携式脑磁装置研制, 2024-01-01 至 2028-12-31

[2] 之江实验室, 自设青年基金, 111012-AA2301, 脑认知启发的人工智能研究, 2023-01 至 2023-12

[3]新加坡大众捷运公司 （Singapore SMRT）, 横向科研项目, -, 用于工程列车调车的 虚拟现实 (VR)培训模拟器 （Virtual Reality (VR) Training Simulator for Shunting of Engineering Trains (VR-TSST)）, 2019-11 至 2021-03

[4] 新加坡民航局（Civil Aviation Authority of Singapore）, 横向科研项目, -, 基 于脑电图的空中交通管制运营商 (ATCO) 的人为因素评估以优化培训（EEG-based Human Factors Evaluation of Air Traffic Control Operators (ATCOs) for Optimal Training）, 2019-02 至 2019-10

[5] 新加坡海事学院（Singapore Maritime Academy）, 横向科研项目, -, 用于海上液化 天然气消防培训的虚拟现实模拟系统（VR-based Liquefied Natural Gas (LNG) firefighting simulation system）, 2019-01 至 2019-08

[6] 新加坡海事与港务管理局（Maritime and Port Authority of Singapore）, 横向科研项目, -, 海事风险管理中的人为因素（Human factors in maritime risk management） , 2018-07 至 2019-06

二、近年来发表的主要论文

[1] Multi-Level Gated U-Net for Denoising TMR Sensor-Based MCG Signals, Z. Xing, H. Li, H. Dou, Z. Zhong, J. Dai, C. Wang, J. Cui(崔健)*, X. Zhang, T. Jiang, International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2025, Accepted. (CCF B，通讯)

[2] Entropy-guided robust feature domain adaptation for electroencephalogram-based cross-dataset drowsiness recognition，L. Yuan, J Cui(崔健)*, R. Li*, Z. Zheng*, MY Siyal, Z Yi，Engineering Applications of Artificial Intelligence (EAAI) 137, 109153，2024(中科院一区 TOP，通讯, IF=8.0)

[3] A benchmarking framework for eye-tracking-based vigilance prediction of vessel traffic controllers，Z. Li, R. Li, L. Yuan, J. Cui(崔健)*, F. Li*，Engineering Applications of Artificial Intelligence (EAAI) 129, 107660, 2024(中科院一 区TOP，通讯, IF=8.0)

[4] SPARK: A High-Efficiency Black-Box Domain Adaptation Framework for Source Privacy-Preserving Drowsiness Detection，L. Yuan, R. Li*, J. Cui(崔健)*, MY Siyal， IEEE Journal of Biomedical and Health Informatics (JBHI), 2024 (中科院二区TOP，通讯, IF=6.7)

[5] EEG-based Cross-dataset Driver Drowsiness Recognition with an Entropy Optimization Network，L. Yuan, S. Zhang, R. Li*, Z. Zheng*, J. Cui(崔健)*, M. Y. Siyal， IEEE Journal of Biomedical and Health Informatics (JBHI), 2024(中 科院二区TOP，通讯, IF=6.7)

[6] A spectral-ensemble deep random vector functional link network for passive brain–computer interface, R. Li, R. Gao, P. N. Suganthan, J. Cui(崔健)*, O. Sourina, L. Wang, et al. Expert Systems with Applications (ESWA) 227, 120279, 2023 (中科院一区TOP，通讯, IF=7.5)

[7] Towards best practice of interpreting deep learning models for EEG-based brain computer interfaces. J. Cui(崔健), L. Yuan, Z. Wang*, R. Li, & T. Jiang, (2023). Frontiers in Computational Neuroscience, 17. (中科院四区，一作, IF=2.3)

[8] R. Li, M. Hu, J. Cui(崔健)*, L. Wang and O. Sourina, Ensemble of randomized neural network and boosted trees for eye-tracking-based driver situation awareness recognition and interpretation, ICONIP 2023 (CCF C，通讯)

[9] J Cui(崔健), L Yuan, R Li, Z Wang, D Yang, T Jiang，Benchmarking EEG-based Cross-dataset Driver Drowsiness Recognition with Deep Transfer Learning, EMBC 2023 (一作)

[10] J. Cui(崔健), Z. Lan, O. Sourina and W. Müller-Wittig, EEG-Based Cross-Subject Driver Drowsiness Recognition With an Interpretable Convolutional Neural Network, in IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023 (中科院一区Top, 一作，IF=8.9)

[11] J. Cui(崔健), Z. Lan, Y. Liu, R. Li, F. Li, O. Sourina, W. Müller-Wittig, A compact and interpretable convolutional neural network for cross-subject driver drowsiness detection from single-channel EEG, Methods, 2022 (中科院三区, 一作，IF=4.3)

[12] J. Cui(崔健), & A. Sourin, Mid-air interaction with optical tracking for 3D modeling. Computers & Graphics, 74, 1-11, 2018 (中科院三区,一作，IF=2.8)

[13] J. Cui(崔健), Q. Pan, Q. Qian, M. He, & Q. Sun, A multi-agent dynamic model based on different kinds of bequests. Physica A: Statistical Mechanics and its Applications, 392(6), 1393-1397, 2013 (中科院二区,一作，IF=3.1)

[14] J Cui(崔健), A Sourin, Interactive shape modeling using leap motion controller, SIGGRAPH Asia 2017 Technical Briefs, 2017 (CCF A, 一作)

[15] J. Cui(崔健), A. Kuijper, D. W. Fellner & A. Sourin, Understanding people's mental models of mid-air interaction for virtual assembly and shape modeling. In Proceedings of the 29th international conference on computer animation and social agents (CASA) (pp. 139-146), 2016 (CCF C, 一作)

三、已授权发明专利

[1] 崔健、薛云龙、张莎莎、王兆祥、郑重、蒋田仔，基于异构图网络的 EEG-fNIRS 运 动想象识别方法和装置，2024.7.26，ZJ-2023-1-000653-CN-02

[2] 崔健、张莎莎、郑重、薛云龙、王兆祥、张军阳，基于动态功能脑网络的大脑视听 融合机制探索方法和装置，2024.7.2，ZJ-2024-1-000839-CN-02

[3] 张莎莎、崔健、郑重、薛云龙、张瑜、王兆祥、张军阳、蒋田仔，一种视听刺激下 的大脑编码方法、装置及介质，2024.8.23，ZJ-2024-1-000875-CN-02

[4] 袁月、王兆祥、崔健、张军阳、张瑜、蒋田仔，一种癫痫患者单通道脑电信号的实 时检测系统，2024.6.4，ZJ-2023-1-333734-CN-02

[5] 郑重、王辰、崔健、张瑜、王兆祥、张军阳、蒋田仔，心磁信号和心冲击信号采集 系统、方法和存储介质，2024.08.13，CN118177812B

[6] 王兆祥、李姗、张军阳、崔健、张瑜、蒋田仔，基于神经电信号的癫痫样棘波处理 方法和装置，2024.03.12，CN117033988B

[7] 郑重、薛云龙、袁立强、崔健、张莎莎、王兆祥、张军阳、张瑜、蒋田仔，基于熵 优化神经网络的跨库脑电疲劳识别方法和系统，2024.7.2，ZJ-2024-1-000901-CN-02

[8] 郑重、薛云龙、袁立强、崔健、张莎莎、王兆祥、张军阳、张瑜、蒋田仔，基于EGRF 模型的跨库脑电疲劳识别方法及装置，2024.7.30，ZJ-2024-1-000890-CN-02

邮箱：cuijian@hit.edu.cn