I am interested in artificial intelligence and theoretical computer science, and especially topics that allow me to leverage algorithmic and combinatorial insights to solve problems with real-world relevance. Areas I am particularly active in include:
Decision-Making in International Relations
The study of how nations and other actors make decisions in conflict and crisis is a major field of interdisciplinary social science research, pulling together ideas from political science, artificial intelligence, game theory, network analysis, and many others. As the use of big data and artificial intelligence in political science and international relations is a relatively new field, there are many foundational and theoretical questions still open. Developing better answers to these questions allows us to understand and predict how conflicts begin and evolve, and how to best prevent them.
Fairness and Bias in Artificial Intelligence
Artificial intelligence and machine learning are widely used to process, predict, and optimize the world. Unfortunately, the success of these techniques at studying the latent information found in large data sets causes them to also identify and mimic systemic and cultural biases in the data they are trained on. As AI and ML techniques become widely used in the world around us, it is imperative that we understand how racism, sexism, and other forms of bigotry influence our data and our algorithms, and that we develop tools and techniques to prevent artificial intelligence from duplicating the same biases.
Graph Theory and Social Network Analysis
From the computer networks that control our finances, to the social networks that define our communities, to the global trade networks that define international relations, networks are a fundamental part of the world around us. I am interested in both theoretical questions in graph theory and graph algorithms, as well as applied questions about how the structure of networks can be used to inform how we understand social connections between people.
Combinatorial Game Theory
Games - both real ones played by humans and artificial ones played by mathematicians - are a source of remarkable complexity. While the bulk of game theory research is done by social scientists, there are a number of questions about formal and natural games that are interesting to the complexity theorist. I am currently working on research pushing the boundaries of what is considered a game in complexity theory and am particularly interested in real-world computable games with non-computable optimal strategies.