The main goal of DAEDALUS is the analysis of the interplay between incorporation of data and differential equation-based modeling, which is one of the key problems in model-based research of the 21st century. DAEDALUS focuses both on theoretical insights and on applications in life sciences (brain-computer interfaces and biochemistry) as well as in fluid dynamics. The projects cover a scientific range from machine learning, mathematical theory of model reduction and uncertainty quantification to respective applications in turbulence theory, simulation of complex nonlinear flows as well as of molecular dynamics in chemical and biological systems. DAEDALUS is a collaboration of Technische Universität Berlin, Freie Universität Berlin and Otto von Guericke University Magdeburg.

LATEST NEWS

Professor Jörn Sesterhenn has accepted the professorship ‘Mechanics and Fluid Dynamics’ at University of Bayreuth. Congratulations!

Professor Jörn Sesterhenn will be mainly engaged in data assimilation. We wish him all the best for the future and congratulate to this achievement!

[2019-09-11]

Congratulations to Professor Frank Noé, Jonas Köhler and co-authors: Paper on Boltzmann Generators published in Science!

We congratulate on the acceptation of the paper ‘Boltzmann generators: Sampling equilibrium states of many-body systems with deep learning’ by Frank Noé, Simon Olsson, Jonas Köhler and Hao Wu.

https://www.fu-berlin.de/en/presse/informationen/fup/2019/fup_19_255-ki-physik/index.html
https://science.sciencemag.org/content/365/6457/eaaw1147

[2019-09-06]

Congratulations – Prof. Kutyniok has been elevated to the grade of IEEE Senior member.

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The IEEE Senior Membership is an honor bestowed only to those who have made significant contributions to the profession. For more information on IEEE see here: https://www.ieee.org/https://www.8ecm.si/program/plenary-speakers

[2019-07-29]