Marie-Abèle is an independent Research Associate at the Department of Statistics, Harvard University. Her research interests focus on developing causal inference methods for quantifying the effects of environmental exposures on health outcomes and understanding the mechanisms explaining these health effects. Her research is funded by the NIH Early Independence Award program
Ibon is a postdoctoral fellow focusing on causal inference for epidemiological studies. He mainly develops R packages and Shiny apps. Prior to Harvard, he worked on childhood and adult cancer, air pollution and exposome. He received a B.S. in Biology and Environmental Sciences, and an M.Sc in Bioinformatics.
Young is a postdoctoral fellow and his research interests are, broadly, point processes, machine learning and Bayesian statistics.
Alice is a PhD candidate in Human Biology at the Ludwig-Maximilian University (LMU) of Munich. At Harvard, she is an Institute Fellow working on applying causal inference methods to understand environmental epidemiology problems. Her projects include the estimation of environmental influences on multiple sclerosis relapses and the human gut microbiome.
Nicole is a statistics PhD student at Harvard University. Her research interests are, broadly, causal inference and experimental design. She is currently funded by NSF GRFP.
Zach is a 5th-year PhD Candidate in Statistics. His work focuses on developing causal inference methods for experiments and observational studies. In particular, his methods (developed inside and outside of MabLab) provide more precise causal inferences than standard methods by conditioning on covariate balance in a randomization-based way. Before Harvard, he received a B.S. in Economics and Statistics and a B.A. in Professional Writing from Carnegie Mellon in 2014.
Marrs is a first year undergraduate student at Harvard College.
A self-taught data visualization whiz, Rachel turns words and data into clear and informative graphics. Rachel holds a Bachelor's degree in Marine Science and Geography from Boston University and a Master's in Statistics from Harvard University. Her broad scientific and startup experience spans the fields of biogeochemistry, genomics, geographic information systems, and speech technology, pointing to her unique talent in communicating through words, numbers, and images.
Stephane is a PhD student in Statistics at Harvard University, working under the supervision of Pierre Jacob. His research interests include Bayesian model comparison and sequential Monte Carlo methods.