I'm currently a postdoctoral researcher at the University of Chicago working on a class of strategies used to accelerate learning the properties of systems simulated with molecular dynamics.
When performing molecular dynamics simulations of materials in chemistry, physics and
biology, there exists a large gap between the time scales that can be probed
computationally to the ones observed in experiments. Two strategies to tackle this
problem are both to develop algorithms to explore the simulation space more efficiently, and to
employ hardware accelerators. I would like to share my experience and perspectives using
Julia to make faster developments in both fronts.