Michael Plainer
Michael Plainer
Doctoral Researcher
Affiliation: BIFOLD, Free University of Berlin, Technical University of Berlin, ELIZA
I am a PhD student at BIFOLD (TU and FU Berlin) funded by the ELIZA Zuse School, where I am working with Frank Noé and Klaus-Robert Müller on AI4Science. My research focuses on generative models for dynamical biophysical systems. I also just love geeking out about all things computer science — from machine learning and physics to weird algorithms and cool hacks.
If you are curious about my work or would just like to chat, feel free to contact me!
- Generative Models
- Molecular Dynamics
- AI4Science
Stefaan Simon Pierre Hessmann, Khaled Kahouli, Stefan Gugler, Michael Plainer, Frank Noé, Klaus-Robert Müller, Niklas Wolf Andreas Gebauer
Generative Pseudo-Force Fields for Molecular Generation
Winfried Ripken, Michael Plainer, Gregor Lied, Thorben Frank, Oliver T. Unke, Stefan Chmiela, Frank Noé, Klaus-Robert Müller
Learning Hamiltonian Flow Maps: Mean Flow Consistency for Large-Timestep Molecular Dynamics
Klara Bonneau, Aldo S. Pasos-Trejo, Michael Plainer, Luca Sagresti, Jacopo Venturin, Iryna Zaporozhets, Alessandro Caruso, Edoardo Rolando, Andrea Guljas, Leon Klein, Maximilian Schebek, Filippo Albani, Raquel López-Ríos de Castro, Zakariya El Machachi, Lorenzo Giambagli, Cecilia Clementi
Breaking the Barriers of Molecular Dynamics With Deep-Learning: Opportunities, Pitfalls, and How to Navigate Them
Michael Plainer, Hao Wu, Leon Klein, Stephan Günnemann, Frank Noé