Human brains and vision-based robotics require intensive computation to recognize visual pattern features in various contexts and augmentations, known as invariant pattern recognition. The hummingbird hawkmoth (Macroglossum stellatarum) similarly uses pattern features on flowers to select suitable foraging sites, with only a fraction of the ‘computational power’. Aiming to understand how they do so with such efficiency, we will use behavioural, neural, and computational methods to uncover the algorithmic basis of (invariant) pattern recognition in insect pollinators.

In a spacetime we have one time dimensions and multiple space dimensions. In our reality we experience three space-like dimensions. Now in differential geometry, nothing keeps us from considering manifolds with multiple time-like dimensions. In this project we study algebraic structures, in particular the group SO(p,q), which describe the dynamics and the geometry of so-called pseudo-Riemannian hyperbolic spaces with at least one time dimension.