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...
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...
Zeyi Wang, PhD is a postdoctoral scholar at Division of Biostatistics, University of California, Berkeley, working with Mark van der Laan and Maya Petersen. His research interests include methods development with targeted maximum likelihood estimation in causal inference, computerized efficient estimation, longitudinal and survival data analysis, as well as reproducibility and clinical trials with brain functional connectivity. He received his PhD in Biostatistics from Johns Hopkins Bloomberg School of Public Health.