Zach is a postdoctoral scholar in the Division of Biostatistics at the UC Berkeley School of Public Health working under Professors Alan Hubbard, Jack Colford, and Mark van der Laan. His work applies Targeted Machine Learning methodology to data from the National COVID Cohorts Collaborative (N3C) to evaluate protective interventions against Long COVID, including COVID-19 vaccination, selective serotonin reuptake inhibitors (SSRIs), metformin, and immune-modulating drugs. He led a research team that placed third in the NIH Long COVID Computational Challenge for building...
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...
Dr. David McCoy, a postdoctoral researcher at CTML, holds a Ph.D. in Environmental Health Sciences from the UC Berkeley School of Public Health, where he was mentored by Alan Hubbard, Alejandro Schuler and Mark van der Laan. His educational background also includes an MSc in Epidemiology, a BA in Philosophy, and a BS in Cognitive Neuroscience. David’s research is rooted at the intersection of causal inference, machine learning, and semiparametric statistical theory. With this multidisciplinary approach, he crafts robust solutions to complex, real-world problems. He has developed...
