Research

My research is application-driven, with a particular emphasis on the medical, biological, and social sciences. I work to develop numerical, data-driven, and mathematical models and methods to solve problems relevant to practitioners. I have worked extensively in cardiological and epidemiological applications, among others.

From 2022 to 2024, I led the CDC’s MACHETES project, leveraging advanced quantitative methods to evaluate the impact of COVID-19 on the U.S. HIV epidemic and to design data-driven interventions aimed at mitigating its adverse effects.

I am currently PI of the University of Urbino DiSPEA project "Problemi nonlineari: teoria, analisi, applicazioni e simulazioni" (Nonlinear problems: theory, analysis, applications and simulations) and the INDAM-GNCS project "Advanced numerical and data-driven methods for PDEs."