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