I am a researcher in infectious disease dynamics where I develop models that combine scientific knowledge and state-of-the-art statistical methods to guide effective policies from noisy, incomplete, and often misleading data. Most of my work concerns COVID-19, seasonal influenza or cholera.
I’m an Assistant Professor at The University of North Carolina at Chapel Hill, working within the Atlantic Coast Center for Infectious Disease Dynamics and Analytics (ACCIDDA), the Insight Net coordinating center. My current projects include:
- Influpaint (GitHub, paper, documentation—start here), where we inpaint epidemic curves generated by denoising diffusion probabilistic models, to produce forecasts of influenza transmission in the U.S.
- RespiLens (GitHub, visit RespiLens) is a convenient web app for exploring local respiratory disease data and forecasts, featuring the latest CDC data. Test your forecasting skills with Forecastle, and explore our toolbox to see how RespiLens can help you analyze disease trends.
- flepiMoP (GitHub), an open-source flexible epidemic modeling pipeline that can simulate most compartmental models over a wide range of connected metapopulation setups. It has been used to track the COVID-19 pandemic and seasonal influenza, providing forecasts and scenarios to decision-makers around the world.
- SMIDDY, aimed to foster the community of infectious disease modelers in Switzerland.
I’m usually working from Chapel Hill in North Carolina. Don’t hesitate to reach out if you pass by the Geneva Lake area, or even if you don’t. Happy to discuss anything 🤔