Position title: PhD Candidate, Neuroscience
Taylor’s research broadly aims to improve our understanding of how brain networks mature through childhood, adolescence, and early adulthood. He is particularly interested in how early-life exposure to interpersonal threat alters typical neurodevelopment and how threat-related stress interacts with the neurobiological mechanisms underlying developmental timing (e.g. when puberty starts, duration of adolescence). He also investigates the clinical utility in using brain maturation and deviations from typical neurodevelopment to make predictions for the diagnosis and treatment of mental illness. His work makes extensive use of structural and functional magnetic resonance imaging (MRI), network theory, and data science/machine learning. Finally, he is an active proponent of Explainable Artificial Intelligence (XAI), a shift toward implementing computational methods that increase transparency in “black box” machine learning, and its applications in neuroscience research.