Hi, I am Guoyang Liu. I received my Ph.D. degree in Engineering from Shandong University in June 2022 and subsequently worked as a postdoctoral researcher at The University of Hong Kong. After completing my postdoctoral appointment, I joined the School of Integrated Circuits, Shandong University in July 2023, where I currently serve as an Assistant Professor and Master's Supervisor. I have also been selected for the Shandong University Young Scholars Future Program. To date, I have published more than 50 research papers in SCI-indexed journals, including IEEE Journal of Biomedical and Health Informatics (JBHI), IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI), IEEE Transactions on Human-Machine Systems (THMS), IEEE Transactions on Instrumentation and Measurement (TIM), npj Science of Learning, and Neural Networks, as well as at EI-indexed international conferences such as ACL and CogSci. I have also been granted multiple Chinese invention patents and Australian standard patents. I am currently the principal investigator of more than ten research and education projects funded by the National Natural Science Foundation of China, the Natural Science Foundation of Shandong Province, the Natural Science Foundation of Guangdong Province, the Natural Science Foundation of Xinjiang, the Shenzhen Natural Science Foundation, key laboratory open funds, and educational reform programs. My honors and awards include the Outstanding Doctoral Dissertation Award of Shandong Province, the Grand Prize of the National Youth Artificial Intelligence Innovation and Entrepreneurship Competition, the Top Ten Innovative Technology Achievement Award of the World Robot Contest, the MATLAB EXPO Research Innovation Award, and the Outstanding Class Advisor Award of Shandong University. I have also supervised students who received the First Prize in the BCI Brain-Controlled Robot Competition of the World Robot Contest, as well as the National First Prize and Corporate Grand Prize in the National College Student Integrated Circuit Innovation and Entrepreneurship Competition. In teaching and educational research, I have published one SCI-indexed paper on educational reform, led one teaching reform project at Shandong University, and received an award in the Shandong University Teaching Innovation Competition as well as the First Prize in the Teaching Case Competition at the National Symposium on AI-Empowered Higher Education. My current research interests include interpretable brain-computer interface hardware and software system design, explainable artificial intelligence (XAI), FPGA-based deep learning hardware accelerator design, large language models, and cognitive science.
Academic Services
- Frontiers in Neuroscience (SCIE indexed), Lead Guest Editor of the Special Issue "Advances in Explainable Analysis Methods for Cognitive and Computational Neuroscience"; submission deadline: February 1, 2026
- Journal of Visualized Experiments (JoVE) (SCIE indexed), Lead Guest Editor of the Special Issue "Advanced Methodologies and Applications of Explainable Artificial Intelligence"; submission deadline: February 1, 2026
- Applied Sciences (SCIE indexed), Lead Guest Editor of the Special Issue "Explainable Artificial Intelligence Technology and Its Applications"; submission deadline: January 1, 2026
- IEEE DLCV 2025 (EI indexed), Workshop Chair for "Deep Learning in Biomedical Signal Processing"; submission deadline: May 10, 2025
- Brain-X Early-Career Editorial Board Member; Member of IEEE, the Cognitive Science Society, CCF, and CAAI; Reviewer for MICCAI, CogSci, Information Sciences, and Expert Systems with Applications, among others
Admissions & Recruitment
Our lab regularly recruits graduate students and research assistants from Computer Science, Electronic Information, Biomedical Engineering, and Psychology/Cognitive Science. We plan to recruit 1–3 M.Sc. students annually and are concurrently hiring 1 Research Assistant on a rolling basis. We welcome motivated candidates with solid programming skills and strong interest in Deep Learning, Explainable AI (XAI), EEG analysis, and Brain–Computer Interfaces (BCI) to join us. If you are interested, please send your CV (including representative work) and a brief statement of research interests using the contact information on this homepage. Our lab is equipped with deep learning servers (multi-GPU) and data storage platforms; we also have a Neuracle 64-channel wireless EEG acquisition system and other experimental devices. We encourage high-quality publications, open-source releases, and academic competitions, and provide opportunities for interdisciplinary training and international collaboration.