Postdoctoral Scholar, University of Chicago
My work in the Knowledge Lab focuses on developing computational models and techniques that assess the production and propagation of credible and replicable scientific knowledge. Using large-scale data sets on scientific claims from the literature and networks of co-authorship and citations, I work to shed light on patterns of social dependencies in science and on processes of assigning credibility to scientific claims, thereby gaining some novel understanding on how knowledge evolves.
My research lies at the intersection of science of science, reproducibility, network science, computational social science, and Bayesian data analysis. I received my PhD from Oxford University, in which I apply computational tools from network science to understand the structure of international migration of people at a global scale. At Oxford, I have also joined Mason Porter's research group on networks at the Mathematical Institute where I have since enjoyed cross-disciplinary conversations with applied mathematicians.