I am a doctoral research working on "Exploring network dynamics with machine learning" as a member of the non-linear dynamics and control group at TU Berlin and of the complex energy networks (COEN) group at PIK.
My current research interests are:
* Graph neural networks
* Simulation of complex networks in Julia (as a package maintainer of NetworkDynamics.jl)
* Optimization via differential programming
Department
Contact
14412 Potsdam
- Scientific machine learning (graph convolutional networks, neural differential equations)
- Complex networks (power grids, brain models)
- Stability and synchronization in dynamical systems
- Scientific computing and open source software (Julia, especially NetworkDynamics.jl)
Lindner, M., & Donner, R. V. (2017). Spatio-temporal organization of dynamics in a two-dimensional periodically driven vortex flow: A Lagrangian flow network perspective. Chaos: An Interdisciplinary Journal of Nonlinear Science, 27(3), 035806.
Donner, R. V., Lindner, M., Tupikina, L., & Molkenthin, N. (2019). Characterizing flows by complex network methods. In A Mathematical Modeling Approach from Nonlinear Dynamics to Complex Systems (pp. 197-226). Springer, Cham.
Lindner, M., & Hellmann, F. (2019). Stochastic basins of attraction and generalized committor functions. Physical Review E, 100(2), 022124
Clisciety - climate science, energy transition and society
The workshop collective clisciety aims at a constructive exchange between climate science and society. We develop educational workshops and talks on climate change and its consequences and establish contact with potential speakers for your event (in German and English).
Zehn Fakten zum Klimawandel - ZEIT online, with Antonia Schuster
I offer courses for beginners in programming (Python, in German and English). Contact me if you are looking for a facilitator.
