My research interests broadly encompass organizational theory, particularly organizational learning and culture. My key research inquiry, across several projects, focuses on the mechanisms that shape organizational cultural clustering, convergence, and diversity in an ecosystem and their broad impact on organizations' propensity and perception of innovation. This requires me to take a relational and multi-level (micro-macro) perspective of various mechanisms, including learning (e.g., cognition, reinforcement, collective decision-making), strategic (e.g., mergers and acquisitions), and sociological mechanisms (e.g., status, embeddedness, mobility, and isomorphism). I find it particularly interesting how the interplay between these mechanisms produces unanticipated but patterned behaviors. 

In my research I use a multi-method approach: computer simulations/game-theoretical models, social network analysis, big data-driven studies (machine learning/NLP), quasi-experiments, and collaboration with psychological experiments/qualitative studies to produce grounded and comprehensive theoretical contributions

How belief dynamics drive structural dynamics, yielding the community-level incompatibility where residentially segregated communities tend to be more socially cohesive (Bao et al., 2022; Neal et al., 2014).

I have a background in evolutionary biology. I believe many of the classical models in organizational learning and collective action can be traced, to a greater or lesser extent, in evolutionary biology and behavioral ecology. The most important lesson biology has taught me is that the group is greater than the sum of its parts. Complex, interdependent dynamics in human organizations that give rise to 'emergent' behaviors are of broad interest to me. I target a number of substantive areas -- centered on my key inquiry -- where collective action and emergent processes are evident (e.g., networks, norms, knowledge, adoption). This viewpoint permits me to broaden the generalizability of these organizational phenomena.

I apply NLP (embedding, topic modeling, semantic networks, etc.) methods to study drift in categorization and knowledge intersectionality.