Hi，我是刘国洋，2022年6月于山东大学获得工学博士学位，并随后于香港大学担任博士后研究员，博士后出站后于2023年7月至今在山东大学集成电路学院任助理研究员、硕士生导师。目前以第一、通讯作者身份在 npj Science of Learning、IEEE THMS / TIM / JBHI、Neural Networks、International Journal of Neural Systems 等SCI期刊，CogSci、IEEE ICHMS 等国际会议发表研究论文三十余篇，并已授权多项国家发明专利；正在主持国家自然科学基金、广东省自然科学基金、山东省自然科学基金、重点实验室开放课题及教改课题等多个项目；获山东省优秀博士论文、世界机器人大会创新技术成果奖、MATLAB EXPO科研创新奖、山东大学优秀班主任等多个荣誉奖项。目前研究领域包括深度学习、可解释人工智能（XAI）、脑电信号分析、脑机接口（BCI）、癫痫检测、虹膜识别、FPGA深度学习硬件加速器设计、眼动分析和认知科学等。
- IEEE会员，认知科学学会（Cognitive Science Society）会员，中国计算机学会（CCF）会员，中国人工智能学会（CAAI）会员，MICCAI、CogSci、Information Sciences、Expert Systems with Applications等期刊审稿人
- IEEE DLCV 2025，“生物医学信号处理中的深度学习”专题研讨会Chair（Workshop "Deep Learning in Biomedical Signal Processing"），投稿截止日期：2025年5月10日
- Applied Sciences (JCR Q1)，“可解释人工智能技术及其应用” 专刊客座编辑（Special Issue "Explainable Artificial Intelligence Technology and Its Applications"），投稿截止日期：2026年1月1日
- Brain-X 青年编委
论文
已发表的期刊论文- G. Liu, Y. Zheng, M. Tsang, J. Hsiao, "Understanding the role of eye movement pattern and consistency during face recognition through EEG decoding," npj Science of Learning, 2025. [pdf]
- G. Liu, S. Ren, J. Wang, W. Zhou, "Efficient Group Cosine Convolutional Neural Network for EEG-based Seizure Identification," IEEE Transactions on Instrumentation and Measurement, 2025. [pdf]
- G. Liu, R. Zhang, L. Tian, W. Zhou, "Fine-Grained Spatial-Frequency-Time Framework for Motor Imagery Brain-Computer Interface," IEEE Journal of Biomedical and Health Informatics, 2025. [pdf]
- G. Liu, J. Zhang, A. Chan, J. Hsiao, "Human Attention-Guided Explainable Artificial Intelligence for Computer Vision Models," Neural Networks, 2024. (Accepted) [pdf]
- G. Liu, L. Tian, Y. Wen, W. Yu, W. Zhou, "Cosine Convolutional Neural Network and Its Application for Seizure Detection," Neural Networks, 2024. [pdf]
- G. Liu, Y. Wen, J. Hsiao, D. Zhang, L. Tian, and W. Zhou, "EEG-based Familiar and Unfamiliar Face Classification Using Filter-Bank Differential Entropy Features," IEEE Transactions on Human-Machine Systems, 2024. [pdf]
- G. Liu, W. Zhou, and M. Geng, "Automatic seizure detection based on S-Transform and deep convolutional neural network," International journal of neural systems, vol. 30, no. 04, p. 1950024, 2020. [pdf]
- G. Liu, X. Han, L. Tian, W. Zhou, and H. Liu, "ECG quality assessment based on hand-crafted statistics and deep-learned S-transform spectrogram features," Computer Methods and Programs in Biomedicine, vol. 208, p. 106269, 2021. [pdf]
- G. Liu, L. Tian, and W. Zhou, "Patient-Independent Seizure Detection Based on Channel-Perturbation Convolutional Neural Network and Bidirectional Long Short-Term Memory," International journal of neural systems, vol. 32, no. 06, p. 2150051, 2022. [pdf]
- G. Liu, L. Tian, and W. Zhou, "Multiscale Time-Frequency Method for Multiclass Motor Imagery Brain Computer Interface," Computers in Biology and Medicine, vol. 143, p. 105299, 2022. [pdf]
- G. Liu, W. Zhou, L. Tian, W. Liu, Y. Liu, and H. Xu, "An Efficient and Accurate Iris Recognition Algorithm Based on a Novel Condensed 2-ch Deep Convolutional Neural Network," Sensors, vol. 21, no. 11, p. 3721, 2021. [pdf]
- G. Liu*, J. Hsiao, W. Zhou, L. Tian, "MartMi-BCI: A Matlab-based Real-Time Motor Imagery Brain-Computer Interface Platform," SoftwareX, vol. 22, p. 101371, 2023. (* corresponding author) [GitHub] [pdf]
- Q. Meng#, G. Liu#, L. Tian, M. Zeng, X. Lu, and J. Yan, "An Improved Vocoder Algorithm Based on Music Harmonics and Time Sampling," Applied Acoustics, vol. 205, p. 109288, 2023. (# co-first author) [pdf]
- R. Zhang, G. Liu, Y. Wen, and W. Zhou, "Self-attention-based Convolutional Neural Network AND Time-frequency Common Spatial Pattern for enhanced Motor Imagery Classification," Journal of Neuroscience Methods, p. 109953, 2023. [pdf]
- X. Zhong, G. Liu, X. Dong, C. Li, H. Li, H. Cui, and W. Zhou, "Automatic Seizure Detection Based on Stockwell Transform and Transformer," Sensors, 2023. [pdf]
- M. Geng, W. Zhou, G. Liu, C. Li, and Y. Zhang, "Epileptic seizure detection based on stockwell transform and bidirectional long short-term memory," IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 28, no. 3, pp. 573-580, 2020. [pdf]
- C. Li, W. Zhou, G. Liu, Y. Zhang, M. Geng, Z. Liu, S. Wang, and W. Shang, "Seizure Onset Detection Using Empirical Mode Decomposition and Common Spatial Pattern," IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 29, pp. 458-467, 2021. [pdf]
- G. Liu, J. Zhang, A. Chan, J. Hsiao, "Human Attention-Guided Explainable AI for Object Detection," The 45st Annual Conference of the Cognitive Science Society (CogSci 2023). (CCF-B, Core-A, EI indexed) [pdf]
- G. Liu, D. Zhang, L. Tian and W. Zhou, "EEG-Based Familiar and Unfamiliar Face Classification Using Differential Entropy Feature," 2021 IEEE 2nd International Conference on Human-Machine Systems (ICHMS), 2021, pp. 1-3. (EI indexed) [pdf]
- A. Yang, G. Liu, Y. Chen, R. Qi, J. Zhang, J. Hsiao, "Humans vs. AI in Detecting Vehicles and Humans in Driving Scenarios," The 45st Annual Conference of the Cognitive Science Society (CogSci 2023). (CCF-B, Core-A, EI indexed) [pdf]
- J. Zhang, G. Liu, Y. Chen, A. Chan, J. Hsiao, "Demystify Deep-learning AI for Object Detection using Human Attention Data," The 46st Annual Conference of the Cognitive Science Society (CogSci 2024). (CCF-B, Core-A, EI indexed) [pdf]
- R. Qi, G. Liu, J. Zhang, J. Hsiao, "Do Saliency-Based Explainable AI Methods Help Us Understand AI’s Decisions? The Case of Object Detection AI," The 46st Annual Conference of the Cognitive Science Society (CogSci 2024). (CCF-B, Core-A, EI indexed) [pdf]
- R. Zhang#, G. Liu#, M. Su, N. Zhang, C. Chen, D. Lv, F. Peng, and W. Zhou, "Motor Imagery EEG Classification with Self-attention-based Convolutional Neural Network," International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS), 2022. (# Co-first author) (EI indexed) [pdf]
- G. Liu, Q. Meng, JH. Hsiao, L. Tian, "EEG-based pitch perception analysis using EEGNet," Oral presentation at 2023 China Biomedical Engineering Conference (2023中国生物医学工程大会), May 20-21, 2023 in Suzhou, China.
- G. Liu, L. Tian, W. Zhou"Cosine Convolutional Neural Network and Its Application for Seizure Detection," Oral presentation at 2024 International Conference on Brain-On-A-Chip (2024片上脑机接口国际会议), April. 19-21, in Tianjin, China.
- G. Liu, J. Zhang, A. Chan, J. Hsiao, "Human Attention-Guided Explainable Artificial Intelligence for Computer Vision Models," Oral presentation at The International Conference of Human Performance Modelling and Augmentation 2023 (HPMA 2023) – The 2nd Human Factors Engineering and Hybrid Intelligence Conference (2023人因建模与增强国际会议-暨第二届人因工程与混合智能创新大会), Aug. 26-27, in Beijing, China.
- G. Liu, Q. Meng, L. Tian, "一种基于深度学习的跨被试被动式音高感知EEG自动分类方法," Oral presentation at The Interdiciplinary Technologies for Auditory Prostheses 2023 (iTAP 2023) (2023 人工听觉技术跨界研讨会), Oct. 13-15, in Nanjing, China.
- Y. Zhao, G. Liu*, "Epileptic EEG Classification Using Time-Frequency Representation and Deep Neural Network," presented at IEEE Engineering in Medicine and Biology Society (IEEE EMBC 2023), July 24-26, 2023 in Sydney. (Poster abstract paper) (* corresponding author)
- Y. Zhao, G. Liu*, "Comparison of time-frequency representations for deep learning-based epileptic EEG classification," Nanosymposium presentation at Neuroscience 2023 (SfN 2023), Nov. 11-15, in Washington, DC. (Abstract) (* corresponding author)
- G. Liu, J. Zhang, A. Chan, J. Hsiao, "Human Attention-Guided Explainable Artificial Intelligence for Computer Vision Models," submitted to International Journal of Computer Vision (IJCV). [pdf]
竞赛
国际竞赛- 刘国洋 (负责人、队长). 指导教师: 周卫东教授、田岚教授.
2020 世界机器人大赛总决赛 – 脑控机器人大赛 二等奖
在世界机器人大赛中A榜/B榜竞赛中均获第二名.
数据库
脑电数据库- SH-SDU 癫痫脑电数据库.
- 收集者: Guoyang Liu; Zhen Liu; Shang Wang; Wei Shang; Minxing Geng; Weidong Zhou*.
- 单位: 山东大学 & 山东大学第二医院.
- 描述: 在SH-SDU数据库中, 从10位患者共191次癫痫发作中，经验丰富的专家通过对177.34小时的脑电图(EEG)记录进行了目视检查并进行了标记。每位患者记录了18个单极通道，参考电极G位于Fz和Cz之间。更详细的研究范式可以参考我们的期刊论文。
- 若您对此数据库感兴趣，可以联系我们。
- SDU Familiar/Unfamiliar Face Recognition EEG Database.
- 收集者: Guoyang Liu; Weidong Zhou*.
- 单位: 山东大学.
- 描述: 该数据库有10名健康的志愿者（年龄在18至25岁之间）参与。设计了一种熟悉/不熟悉的面孔识别脑电图（EEG）范式。详细范式可以参考会议论文。
- 若您对此数据库感兴趣，可以联系我们。 - 我们还拥有更多的EEG数据库，例如运动想象（左/右手/肘部）EEG数据库（22名参与者），以及虹膜识别数据库（200名参与者）。若您对此数据库感兴趣，可以联系我们。
软件
- AI & 人类注意力解释分析器 （SS）
开发人员: G. Liu, Janet H. Hsiao
- MartMi-BCI - 运动想象BCI平台 （GitHub）
开发人员: G. Liu, Weidong Zhou, Lan Tian, Janet H. Hsiao
- 虹膜识别 - 注册 & 管理 & 屏保
开发人员: G. Liu, Weidong Zhou, Lan Tian
- EEG分析与自动癫痫检测工具箱
开发人员: G. Liu, Weidong Zhou
