Aaron graduated from Carnegie Mellon University in 2023, where he obtained an honors B.S. in chemical engineering and a master of chemical engineering concurrently. As an undergraduate, Aaron worked with Professor Zachary Ulissi on the use of large graph neural network models to predict the properties of transition metal complexes, both from the dataset development and machine learning model training sides. He joined the Kulik group in December 2023 as a Ph.D. student in chemical engineering. His research interests involve the use of machine learning techniques to better understand quantum chemical modeling, as well as the use of models for materials design.