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.