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.
Selected Publications
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A mechanochemical model recapitulates distinct vertebrate gastrulation modes
M. Serra, G. S. Nájera, M. Chuai, A. M. Plum, S. Santhosh, V. Spandan, C. J. Weijer, and L. Mahadevan
Science Advances 9.49 (2023) [PDF] Featured image in Science Advances, UCSD News
Spike formation theory in three-dimensional flow separation
S. Santhosh, H. Qin, B. F. Klose, G. B. Jacobs, J. Vétel, and M. Serra
J. Fluid Mech. 969, A25 (2023) [PDF]
Defect-mediated dynamics of coherent structures in active nematics
M. Serra, L. Lemma, L. Giomi, Z. Dogic, and L. Mahadevan
Nature Physics 1-7 (2023) [PDF]
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Search and rescue at sea aided by hidden flow structures
M. Serra, P. Sathe, I. Rypina, A. Kirincich, S. Ross, P. Lermusiaux, A. Allen, T. Peacock, and G. Haller
Nature Communications 11 2525 (2020). [PDF] MIT News, NSF, Sci. Amer., BBC, AMS, Science Journal for kids
Dynamic morphoskeletons in development
M. Serra, S. Streichan, M. Chuai, C. J. Weijer, and L. Mahadevan
PNAS 117.21 (2020) [PDF] Harvard SEAS News, SIAM News
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Objective Eulerian coherent structures
M. Serra and G. Haller
Chaos 26 (2016) 053110. [PDF] Editor's pick
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