John earned his Bachelor’s degree in Measurement and Control Technology and Instrumentation, followed by a Ph.D. in Instrument Science and Technology. His research interests encompass artificial neural networks, EEG, brain-computer interfaces, machine learning, and medical image processing. With a deep enthusiasm for neuroscience, John strives to integrate artificial neural networks with cognitive neuroscience to achieve a more comprehensive understanding of the brain.
In his leisure time, he is proficient in badminton and squash, enjoys hiking, and delights in exploring local scenic spots or trying new cuisines with friends.