Dr. Fiona Molloy is a computational cognitive neuroscience whose leverages computational models to better understand individual differences in the human brain and behavior. Her main area of focus is the neurocognitive mechanisms underlying addiction, which she studies using neuroimaging (primarily functional magnetic resonance imaging, or fMRI) and decision-making tasks from psychology. She is particularly interested in risk factors for problematic substance use in adolescence, with the long-term goal of early identification and early intervention, before problems arise. She is also interested in building multi-modal models to formally link neural and behavioral measures, and in developing robust methodology for studying individual differences in psychology and neuroscience.
Fiona applies methods and techniques across data science and AI, including Bayesian methods, machine learning, graph-based methods, and mathematical and statistical modeling, with applications bridging behavioral, biological, and healthcare sciences. As a MIDAS postdoctoral affiliate, Fiona will receive further exposure interdisciplinary approaches to computational modeling and training in cutting-edge techniques necessary for complex analyses of high-dimensional, largescale datasets. Her main appointment is in the Addiction Center in the Department of Psychiatry, under the mentorship of Dr. Chandra Sripada and Dr. Alex Weigard. She received her PhD in Cognitive Neuroscience and Masters degrees in Applied Statistics and Cognitive Psychology from The Ohio State University.