Guoyang Liu
Research Associate
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Personal Information:
  • Name (English):
    Guoyang Liu
  • Name (Pinyin):
    liuguoyang
  • E-Mail:
    gyliu@sdu.edu.cn
  • Date of Employment:
    2023-07-24
  • School/Department:
    Shandong University
  • Administrative Position:
    Asistant Researcher
  • Education Level:
    Postgraduate (Postdoctoral)
  • Business Address:
    山东大学软件园校区
  • Gender:
    Male
  • Contact Information:
    Email: gyliu@sdu.edu.cn
  • Degree:
    Doctoral Degree in Engineering
  • Status:
    Employed
  • Alma Mater:
    Shandong University
Biography

I received my Ph.D. degree in school of Microelectronics, Shandong University, China, in 2022. In 2022-2023, I worked as a Post-Doctoral Fellow in Department of Psychology, University of Hong Kong, Hong Kong. My current research fields include Deep Learning, eXplainable Artificial Intelligence (XAI), EEG Analysis, Brain-Computer Interface (BCI), Seizure Detection, Iris Recognition, FPGA-based Deep Learning Hardware Accelerator Design, Eye Movement Analysis and Cognitive Science. Currently, I'm serving on the Young Editorial Board of journal Brain-X.


Personal Homepage: http://guoyang.work/ 

Publication
Papers

1. 张睿. Self-attention-based convolutional neural network and time-frequency common spatial pattern for enhanced motor imagery classification .Journal of Neuroscience Methods.2023,398

2. 刘国洋. An Efficient and Accurate Iris Recognition Algorithm Based on a Novel Condensed 2-ch Deep Convolutional Neural Network .Sensors.2021 (11)

3. 刘国洋. Multiscale Time-Frequency Method for Multiclass Motor Imagery Brain Computer Interface .Computers in Biology and Medicine.2022 (143)

4. 刘国洋. MartMi-BCI: A Matlab-based Real-Time Motor Imagery Brain-Computer Interface Platform .SOFTWAREX.2023 (22)

5. 刘国洋. Automatic seizure detection based on S-Transform and deep convolutional neural network .International Journal of Neural Systems.2020,30 (4)

6. 刘国洋. ECG quality assessment based on hand-crafted statistics and deep-learned S-transform spectrogram features .Computer Methods and Programs in Biomedicine.2021 (208)

7. 刘国洋. Patient-Independent Seizure Detection Based on Channel-Perturbation Convolutional Neural Network and Bidirectional Long Short-Term Memory .International Journal of Neural Systems.2022 (6)

8. 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.2023,45

9. 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.2023,205 :109288

10. G. Liu*, J. Hsiao, W. Zhou, L. Tian. MartMi-BCI: A Matlab-based Real-Time Motor Imagery Brain-Computer Interface Platform .SoftwareX.2023,22 :101371

11. 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.2022,32 (6):2150051

12. G. Liu, L. Tian, and W. Zhou. Multiscale Time-Frequency Method for Multiclass Motor Imagery Brain Computer Interface .Computers in Biology and Medicine.2022,143 :105299

13. 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.2021,208 :106269

14. 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 :1-3

15. 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.2021,21 (11):3721

16. G. Liu, W. Zhou, and M. Geng. Automatic seizure detection based on S-Transform and deep convolutional neural network .International journal of neural systems.2020,30 (4):1950024

Patens
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