Physics-informed machine learning

Computing Contact Problems with Self-Conforming Hybrid Materials

Realize a novel hybrid material that self-conforms around an object of interest as a physical route for computing and reporting the object’s shape.

Using data science to discover materials with extreme properties.

Discovery of high-temperature, oxidation resistant, complex, concentrated alloys via data science driven multi-resolution experiments and simulations.

Physics-Informed LeaRnIng for Multiscale Systems (PILgRIMS)

Baking known physics into machine learning algorithms.