CECAM Workshop: Recent Advances in Machine Learning Accelerated Molecular Dynamics

This CECAM workshop aims at bringing scientists from Molecular Dynamics simulation and Machine Learning backgrounds within the broad and simulation-intense areas of biophysics and material science under the same roof to spark discussions and new ideas.

The workshop aims at bringing scientists from Molecular Dynamics simulation and Machine Learning backgrounds within the broad and simulation-intense areas of biophysics and material science under the same roof to spark discussions and new ideas. In particular, leading questions that we would like to address in this workshop are as follows:

• How to include prior knowledge such as symmetries, specific boundary conditions, quantitative observations and covariant requirements, and long-range interactions into atomistic ML models?
• How to develop the synergy between advanced sampling methods and ML methods?
• How to combine knowledge from massively large, heterogeneous and/or  experimental/MD simulation datasets with ML in order to identify novel targets in material (e.g. for a new material design in all-solid-state batteries) and drug design (e.g. in a responsive mode as was shown to be necessary for the Covid-19 pandemic)?

Organizers:

• Prof. Giuseppe Brancato
  Scuola Normale Superiore, Pisa, Italy
• Prof. Paolo Carloni
  Forschungszentrum Jülich and RWTH Aachen University and JARA, Germany
• Prof. Kersti Hermansson
  Uppsala University, Sweden
• Prof. Giovannimaria Piccini
  Humboldt Universität zu Berlin - Max Planck Gesellschaft, Berlin, Germany
• Prof. Andrew Plested
  Leibniz-Institut für Molekulare Pharmakologie, Berlin, Germany
• Dr. Chao Zhang
  Uppsala University, Sweden