Many biological systems function through the concerted behavior of
many connected elements in a self-organised manner, very much like
spontaneous ordering and phase transitions in physics. The recent
years have witnessed a large increase in the amount of detailed
multi-variate data in a variety biological contexts (genomics,
electrophysiology, fluorescence microscopy, etc.), offering a unique
opportunity to learn these mechanisms of self-organisation directly
from data. In my research I study the behaviour of complex biological
systems that show interesting emergent phenomena, in immunology,
neuroscience, cellular biology, and collective behaviour. I combine a
bottom-up approach, in which mechanisms of organisation are
hypothesized from efficient design principles, and a top-down
approach, where the local rules of interaction are learned from data
using statistical learning and statistical physics techniques. I'm
particularly interested in three fascinating systems where collective
effects play an important role:
- Population coding of visual information by retinal ganglion cells.
- Dynamics, diversity, and organization of immune receptor repertoires.
- Collective behaviour in bird flocks and bacterial micro-colonies.
