My research interests lie broadly in AI-driven drug discovery, with a particular interest in psychopharmaceuticals. Currently, I am exploring the use of Linear Response Theory on Ligand Gated Ion Channels in hopes of building an algorithm which can derive the necessary binding forces to cause agonism, antagonism, and even partial agonism to a high specificity. Current methods of AI-driven drug disovery, such as Quantitative Structure-Activity Relationship (QSAR), require a large database of pre-existing counterparts without consideration of target proteins, inhibiting the automated discovery of pharmaceuticals with novel functions. We hope to use normal mode analysis with parallel tempering monte carlo molecular dynamics to train a rudimentary artificial intelligence to predict the functional movements of proteins.