Daniel Schwalbe-Koda
Assistant Professor, Materials Science and Engineering

Daniel Schwalbe-Koda is an assistant professor of materials science and engineering. He joined UCLA Samueli in 2024 and teaches undergraduate courses in general materials science and physics of materials, and a graduate class in machine learning for predictive materials science. His research group develops computational models for materials synthesis and autonomous characterization.

As a teacher, Schwalbe-Koda takes an “intuition-first” approach, incorporating experimental demonstrations, interactive visualizations, simulations or case studies into his lectures — including an online game he programmed as a review of electrostatics.

He has consistently received top scores in student evaluations, including the highest rating from every respondent in his graduate course. Several students shared that they incorporated the machine learning concepts he taught into their thesis research.

Schwalbe-Koda routinely updates his courses to reflect developments in rapidly evolving fields, often incorporating relevant research published just days before a lecture. He devotes time to improving his teaching and sharing best practices with colleagues across UCLA Samueli. With support from a UCLA Teaching and Learning Center grant, Schwalbe-Koda has also been exploring new ways to teach artificial intelligence to non-computer science students.

His honors include a Department of Energy Early Career Award, recognition on the 2023 Forbes 30 Under 30 Science list, a fellowship from Lawrence Livermore National Laboratory and a merit award from the Brazilian Ministry of Defense.

Schwalbe-Koda received his bachelor’s degree in electronics engineering and master’s degree in physics from the Aeronautics Institute of Technology in Brazil, and a Ph.D. in materials science and engineering from the Massachusetts Institute of Technology.