Daniel joined the group in December 2019 as a Ph.D. student in chemical engineering, having graduated from UC Santa Barbara with a B.S. in chemical engineering and a minor in physics. As an undergraduate, Daniel primarily worked on modeling LaMer burst nucleation in the Peters group. They became interested in electronic structure theory while using DFT for a computational study on CO₂ reduction catalysts in Martin Head-Gordon’s group at UC Berkeley. Daniel’s current research in the Kulik group focuses on the development and application of mathematical models which relate the properties of transition metal complexes beyond simple additivity. They are interested in combining machine learning methods with mathematical modeling to achieve greater prediction accuracy at reduced data cost.