UAlberta Math Biology Seminar: Shan Gao

Tipping points (critical transitions) are abrupt, often irreversible shifts in dynamical systems that can be triggered by small changes. This talk tackles two questions: how to predict tipping early and why tipping occurs. In this talk, I will demonstrate how combining tipping-point ideas with machine learning can enhance early-stage outbreak prediction using limited epidemic data. I will then present a new mechanism, frequency-induced tipping, where a system can be driven to a critical transition by subthreshold periodic forcing at particular frequencies, even in the absence of noise and without crossing a staticbifurcation threshold.