Applications:
Earth Science and Ecology, Informatics, Social Science
Methodologies:
Bayesian Methods, Causal Inference, Graph-Based Methods, Machine Learning, Networks, Statistics

Abigail Jacobs

Assistant Professor

Information, School of Information
Complex Systems, College of Literature, Science, and the Arts

Assistant Professor of Information, School of Information and Assistant Professor of Complex Systems, College of Literature, Science, and the Arts

I am interested in how governance, communities, and inequality emerge in sociotechnical systems, and how the structure of sociotechnical systems encodes and reinforces these processes. To those ends, I develop empirical data and computational methods, focusing on latent variable models; statistical inference in networks; empirical design to study governance in organizations, platforms, and computational social systems; and causal inference and measurement in observational data.

Several sample projects:
> developing empirical populations of networks to infer social and ecological processes encoded in networks
> using probabilistic methods to infer the structure and dynamics of the illicit wildlife trade
> building from theory from political science, statistics, and education to disentangle issues of “bias” in computational systems


Accomplishments and Awards