Hi, I am Guoyang Liu. I received my Ph.D. in Engineering from Shandong University in June 2022 and subsequently served as a Postdoctoral Researcher at The University of Hong Kong. Since July 2023, I have been an Assistant Professor (Researcher) and Master’s Supervisor at the School of Integrated Circuits, Shandong University. As first or corresponding author, I have published 20+ research papers in SCI-indexed journals such as npj Sci. Learn., IEEE THMS / TIM / JBHI, Neural Netw., and Int. J. Neural Syst., as well as at international conferences including CogSci and IEEE ICHMS. I also hold multiple granted Chinese invention patents. I am currently PI of several projects, including National Natural Science Foundation of China, the Natural Science Foundations of Guangdong and Shandong, key laboratory open funds, and teaching reform grants. Honors include the Shandong Province Excellent Doctoral Dissertation, the World Robot Conference Top Ten Innovation Achievement Award, and the MATLAB EXPO Research Innovation Award. My current research interests include deep learning, explainable artificial intelligence (XAI), EEG signal analysis, brain–computer interfaces (BCI), seizure detection, iris recognition, FPGA-based deep learning accelerators, eye-movement analysis, and cognitive science.

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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.

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