My research is targeted toward trying to find long complicated equations which can approximate all of the physical properties of a certain material. To accomplish this, my students spend long hours gathering and curating data from quantum mechanics simulations, developing machine learning models, and running simulations to try to make the models explode. If the models do explode, then the machine has not learned how the material works correctly (unless the material really is explosive). Then I have to figure out a better way to teach the computer how materials work. Currently, I am focused on using these machine learning models to better understand how to make (non-explosive) magnesium alloys which resist cracking, how to make polycarbonate sheets stronger using fiber additives, and how to simulate magnetic materials at the atomic scale.
For all publications, download my curriculum vitae