Research

I come from a customer relationship management (CRM) background, and much of my early work has been inspired by this perspective, developing methodologies for data fusion, selection correction, and causal inference in modeling customer purchase decisions. More generally, I am interested in developing methodologies that allow for the analysis of complex and/or non-standard data structures, such as representation learning methods for unstructured data.

Recently, I am also interested in competitive video games (e-sports) as an empirical context to study strategic human behavior. Currently, I am studying competitive decisions in an e-sports context, developing representation learning tools to enable behavioral analysis of how agents learn and make strategic decisions based on past experience in games with large/complex action spaces.

Working Papers

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Published and Forthcoming Papers

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