Forecasting Covid-19 Dynamics

This research project focuses on building diverse methods using data-driven machine learning techniques to improve forecasting of COVID-19 dynamics. In particular we are evaluating utility of topological predictors from satellite observations to model the current and future COVID-19 spatio-temporal progression and clinical severity of the disease.


Ignacio Segovia-Dominguez
Ignacio Segovia-Dominguez
Visiting Scientist / Postdoctoral Research Associate

My research interests include topological and geometric methods in statistics and machine learning, analysis of complex dynamic networks, evolutionary computation, and computational statistics.