I am currently a faculty member at Fordham Law. My primary research interests are in privacy and cybersecurity law, data science, and public policy. I am particularly interested in using methods drawn from machine learning, natural language processing, and causal inference to explore open questions in law and technology. I also have a number of projects that integrate data science methods into empirical legal studies more broadly.

Prior to arriving at Fordham, I held a number of academic positions. I was a postdoctoral research fellow at NYU's Information Law Institute, a postdoctoral scholar at UC Berkeley's Social Science Data Lab (D-Lab), and a visting postdoc at ETH Zurich's Center for Law and Economics. I earned my PhD at Berkeley Law, where I specialized in Law & Economics, JD at Yale Law School, and BA in Political Science and History from Rutgers University - New Brunswick. I was also a Google Policy Fellow at Engine, a Data Science for Social Good Fellow at the University of Chicago, and a Technology Policy Intern at GitHub.

At Fordham, I currently offer 1L Torts and a survey course on Law & Technology. Previously, I taught or assisted with various undergraduate, law, and graduate courses in both law and data science. I co-taught a Data, Prediction, and Law course for the Berkeley undergraduate Legal Studies and Data Science programs, and a doctoral course in Computational Social Science at Berkeley.

For more details, please see my CV .