About

I am currently a postdoctoral researcher at the Université de Montréal, working in the SIMEXP lab.

As a psychologist and computational neuroscientist, my work focuses on developing methods to characterize complex, naturalistic cognition in health and disease. Specifically, my current projects aim to model individual brain activity across a range of cognitive states—and to assess the generalizability of these individualized models—by extending statistical methods for human neuroimaging data analysis.

My background is in cognitive neuroscience, with a Ph.D. in neuroscience from McGill University as well as Bachelors and Masters degrees in developmental psychology from Cornell University. My dissertation focused on benchmarking emerging methods to compare functional activations during complex cognitive tasks. I previously completed a Wu Tsai Interdisciplinary postdoctoral fellowship at Stanford University, where I worked on developing new methods for handling inter-individual variability in neuroimaging time series.

As part of my research, I help to develop several tools used across the open Python ecosystem such as Nilearn and fmralign. I'm also actively involved in community initiatives to promote open, interdisciplinary science.