Summary
Yu Zhang is an IVADO Postdoctoral Fellow and neuroscientist-engineer who applies deep learning to decode cognition and behavior from structural, functional, and diffusion MRI. With a PhD in Pattern Recognition and over nine years of neuroscience research spanning McGill, the Montreal Neurological Institute, and Université de Montréal, he combines rigorous connectivity-focused neuroimaging expertise with hands-on coding in Matlab, R, and Python and familiarity with TensorFlow, Keras, and PyTorch. His work includes modeling dopamine circuits and Parkinson’s-related behaviors and aims toward real-time brain decoding and simulation for improved brain–computer interfaces. Notably, his PhD-era brain parcellation and multi-modal connectivity methods—born from collaborations in China and Germany—continue to influence his deep learning pipelines for predicting human cognition.
9 years of coding experience