We develop data-driven methods and mathematical models to study complex biological and physical systems, mostly defined through experimental dynamical data sets. These systems are typically nonlinear, multi-scale and chaotic, thus require new ideas to 1) best uncover the underlying causal mechanisms from their footprint on data, and 2) predict their behavior from the essential driving processes. 

Morphogenesis & Active Matter

Coherent Structures

Flow Separation

Latest News

May 26, 2020

Search and rescue at sea aided by hidden flow structures, just appeared in Nature Communications

 - Paper, Editor's Highlight, featured on MIT News and ETH News 

May 07, 2020

Our paper Dynamic morphoskeletons in development, just came out in PNAS

 - Paper, featured on Harvard SEAS News​ and to appear in SIAM News

January 31, 2019

Our Polar Vortex work on Forbes

December 19, 2018

ETH Medal Award for outstanding Doctoral Thesis

April 25, 2018

(in partnership with the Rhodes Trust)  More about the fellowship 

Press releases: PR Newswire,  Forbes 

 

 

 

 

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