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The overarching goal of my research is to understand how we can combine code, data, and law to better model, measure, and manage complex systems (e.g., contemporary information societies). To this end, I explore novel ways of connecting computer science and law, such as using algorithms to collect and analyze legal data as networks, or formalizing and implementing legal and mathematical desiderata for responsible data-centric machine learning with graphs. Currently, I am particularly interested in computational legal theory – i.e., (1) designing computational methods to build a data-driven theory of legal systems and (2) understanding legal systems as computational systems – with implications for how we approach challenges like regulating AI, protecting democratic institutions, and realizing the sustainability transition.