Predicting critical transitions from data

• Grant number: 25/25338-1
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: December 01, 2025
• End date: November 30, 2026
• Field of knowledge: Physical Sciences and Mathematics - Mathematics - Applied Mathematics
• Principal Investigator: Tiago Pereira da Silva
• Grantee: Moacir Aloisio Nascimento dos Santos
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Associated research grant: 23/13706-0 - EPSRC-FAPESP predicting critical transitions in complex dynamical networks: reduction and learning, AP.TEM

Abstract

We will combine the mathematical insights obtained from Objective 1 and the sophisticated reconstruction approachesdeveloped in Objective 2; together with insights from bifurcation theory, we will identify critical transitions and theirearly warning signals from data. This is a highly ambitious and nontrivial challenge. We will address this first at thelevel of synthetic model data, but also test our methodology on real experimental observations. (AU)