Research​

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My lab studies how pathogens and opinions spread on complex systems. My work engages with network science, dynamical systems, social contagion, infectious diseases, and open-source development. My research falls under the broad umbrella of dynamics on complex systems and often examines the interplay between a system's structure and its dynamics. My main research interests are the following:

• Dynamical processes on complex systems: Studying contagion spread on social networks, whether that contagion is an idea or an illness, is important in understanding the epidemics that affect our daily lives. Social networks often include group (higher-order) interactions, and infection or opinion adoption mediated by these interactions can change the dynamics of these systems in meaningful ways.

• Measuring and inferring network structure: The choices we make when collecting network data and the models we choose to represent and fit these data affect the conclusions that we draw. My lab uses Bayesian inference to infer model parameters and network structure from various data sources.

• Open-source software: Software supporting higher-order network science is important for cross-disciplinary research and I created and currently maintain the XGI and HyperContagion libraries as tools for researchers working with higher-order networks.

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