Betsy Ogburn is Associate Professor of Biostatistics at Johns Hopkins Bloomberg School of Public Health. She is also a member of the Institute for Data-Intensive Engineering and Science at Johns Hopkins University and affiliated faculty of the Center for Causal Inference at University of Pennsylvania. She develops methods for learning causal relationships from non-experimental data. A major focus of her work is causal and statistical inference for social network data, with applications to the spread of beliefs and behavior and collective decision-making. Betsy completed her Ph.D. in Biostatistics at Harvard University and is a 2016 National Academy of Science Kavli Fellow. Her website can be found here.
