Daniel Schwalbe-Koda

Daniel Schwalbe-Koda is a PhD candidate in the Department of Materials Science and Engineering at MIT, and a 2020-2021 MIT Energy Fellow. His research combines high-throughput calculations, density functional theory and statistical learning to accelerate the synthesis and design of heterogeneous catalysts and molecular sieves. He also develops machine learning methods for differentiable atomistic simulations, and applies human-computer interaction to materials design.