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Dr. Maximilian Seyrich
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Kontakt:
Büro EW280
Telefon +49 30 314-29050
Adresse Sekr. EW 7-1
Institut für Theoretische Physik
Technische Universität Berlin
Hardenbergstr. 36
D-10623 Berlin
Email seyrich (a) tu-berlin.de
Research interests
- Nonequilibrium Statistical Physics and Biological Physics
- Individual and collective behaviour of active swimmer (Bacteria, Janus particles) performing chemotaxis
- Methods: SDE's, Bayesian inference methods, machine learning (supervised learning and reinforcement learning)
Publications
Traveling concentration pulses of bacteria in a generalized Keller-Segel model
New J. Phys. 21, 103001 (2019)
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Julian Stürmer, Maximilian Seyrich, and Holger Stark
Chemotaxis in a binary mixture of active and passive particles
J. Chem. Phys. 150, 214901 (2019)
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Maximilian Seyrich, Zahra Alirezaeizanjani, Carsten Beta, and Holger Stark
Statistical inference of bacterial chemotaxis strategy
New J. Phys. 20, 103033 (2018)
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Oliver Pohl, Marius Hintsche, Zahra Alirezaeizanjani, Maximilian Seyrich, Carsten Beta, and Holger Stark
Inferring the chemotactic strategy of P. putida and E. coli using modified Kramers-Moyal coefficients
PLoS Comput. Biol. 13, 1 (2017)
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Micro-foundation using percolation theory of the finite time singular behavior of the crash hazard rate in a class of rational expectation bubbles
Int. J. Mod. Phys. C 27, 1650113 (2016)
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Talks
Bacterial chemotaxis: From individual to collective dynamics
Workshop of GRK 1558, 2017, Templin
Statistical inference of bacterial chemotaxis strategies
DPG Spring Meeting, 2017, Dresden
Statistical inference of bacterial chemotaxis strategies
Workshop of GRK 1558, 2016, Bad Schandau-Krippen
Theses
Percolation Theory Applied to Financial Markets: A Cluster Description of Herding Behavior Leading to Bubbles and Crashes
Master Thesis ETH Zürich, 2015
Prof. Dr. Didier Sornette
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Bose-Einstein-Condensation and the U(1)-symmetry group
Semester Thesis ETH Zürich, 2014
Dr. Philipp de Forcrand