Abstract
Major progress in experimental micro-nanofluidics over the last decades has spawned the opportunity to explore new states of droplet-based soft flowing matter, such as microfluidic crystals, high-density confined emulsions, bijels, as well as various types of soft granular flows. These novel states of soft matter raise fundamental challenges to non-equilibrium statistical physics mostly on account of strong nonlinear and nonlocal effects, which set their mechanical and rheological properties far apart from those of the three fundamental states of matter (solid,liquid and gas) they are made of. In this talk, I shall present selected computer simulations and machine-learning algorithms which help shedding light into these fascinating states of soft flowing matter and lay the ground for future applications in science and engineering.
