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Synopsis

From blood circulation to neural activity, fluid flows play a central role across natural and biological systems. However, the nonlinear behaviors that govern these flows remain among the most challenging to describe, model, and observe experimentally. This presentation will explore two complementary strategies for gaining insight into such dynamics: a bottom-up view focused on individual particle motion, and a top-down view centered on the behavior of entire flow networks.

Using holographic microscopy, we can resolve a particle’s shape and trajectory in three dimensions as it flows through a microchannel, revealing how morphology influences motion. In parallel, physical learning offers a powerful statistical framework for investigating how biological flow networks adapt, while electrical analog systems provide an experimental platform for probing the relationship between local and global nonlinearities. Together, these approaches create a more integrated understanding of complex flow phenomena and offer new perspectives on the principles that underlie biological function and adaptation.