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2018 Fellow

Mattia Serra

Nonlinear Dynamics

PhD Institution
ETH Zurich
Postdoctoral institution and lab

The Applied Math Lab

Harvard University

Next Steps

Swiss National Foundation Postdoc Mobility Fellowship at Harvard University
Assistant Professor, Serra Group, University of California, San Diego

Mattia develops mathematical techniques to understand turbulent and unpredictable change in the world. He completed his PhD in nonlinear dynamics at ETH Zurich, Switzerland, having previously studied in his home country, Italy, China, and the Netherlands. As a Schmidt Science Fellow, Mattia worked with L. Mahadevan at Harvard to switch his mathematical modeling from physical systems to biological systems, including human embryonic development. He now continues his work at Harvard as a Swiss National Foundation Postdoc Mobility Fellow.

Mattia’s mathematical models have already proven their value in collaborations with organizations such as MIT and the US Coastguard, where uncovering coherent attractors in the ocean can help to direct search and rescue operations. As a Schmidt Science Fellow, he applied this knowledge to complex biological systems and the modeling of cell flows during the early development of growing embryos. The work has the potential to better understand embryonic development, detect pathological embryos early, as well as uncover the driving mechanisms behind embryogenesis.

Now as Assistant Professor at the University of California, San Diego, Serra’s Group develops 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, and so require new ideas to best uncover the underlying causal mechanisms from their footprint on data, and predict their behavior from the essential driving processes.

As part of our We are Schmidt Science Fellows film series, watch Mattia’s video and read his feature – Organizing Chaos – Using maths to identify coherency in chaotic systems here.