Marie is a postdoctoral fellow in the Divisions of Biostatistics and Epidemiology at the UC Berkeley School of Public Health, where she is mentored by Professors Maya Petersen and Mark van der Laan. Her research interests span statistical learning, causal inference, and network science, with a focus on their applications in medicine and public health.
Her dissertation evaluated the potential of repurposing antidiabetic and antihypertensive medications to prevent or delay the onset of Alzheimer’s disease and related dementias, through the retrospective analysis of data from electronic health records. At the CTML and Kaiser Permanente, she is scaling this effort to study other commonly prescribed drug classes (e.g., obesity medications, antidepressants) and tackle additional disease areas.
During her doctoral studies, Marie also collaborated with the Massachusetts Department of Public Health and Moderna to assess the impact of local vaccine companion programs on vaccine uptake across generations and simulate their national implementation using agent-based models. More recently, she has been investigating the extent of sociodemographic and geographical disparities in substance use-related excess mortality in the US – a project she hopes to continue at the CTML, in partnership with the California Department of Public Health.
Previously, Marie worked as a data scientist at Microsoft, where she analyzed the impact of technology use and digital collaboration on student academic outcomes and socio-emotional learning in school networks, in the presence of treatment spillovers.
Marie earned her PhD in Social & Engineering Systems and Statistics from MIT, and her MSc in Computational and Mathematical Engineering from Stanford University.
Target trial emulation; instrumental variable analyses; mediation analysis; agent-based simulation; drug repurposing; social determinants of health and disparities; infectious diseases; cardiovascular diseases; substance use; mental health
