Bryan R. Goldsmith

Bryan R. Goldsmith is an Associate Professor of Chemical Engineering at the University of Michigan, Ann Arbor, where he also serves as Associate Chair for Graduate Education. He joined the Department in 2017 and was promoted to Associate Professor with tenure effective September 1, 2023. His academic journey includes a BS in Chemical Engineering from the University of California Riverside (2010) and a PhD in Chemical Engineering from the University of California Santa Barbara (2015), followed by a Humboldt Postdoctoral Fellowship at the Fritz Haber Institute of the Max Planck Society in Berlin, Germany.

Prof. Goldsmith's research focuses on applying electronic-structure theory, molecular simulation, and data science tools to understand and design catalysts and materials for sustainable chemical conversion, pollution reduction, and energy generation/storage. His lab combines quantum mechanical modeling, molecular simulation, and machine learning to address major societal challenges in energy and the environment.

His research spans four primary thrusts: (i) Thermo- and electro-catalysis for CO₂ and water pollution remediation; (ii) Machine learning to accelerate catalyst design and discovery; (iii) Catalysis and materials for renewable energy generation, storage, and use; and (iv) Electrocatalytic conversion of bio-oils for sustainable fuel production. These research areas directly address critical sustainability challenges through computational approaches.

Prof. Goldsmith has received numerous prestigious awards including the NSF CAREER Award (2023), the 1938E Award from the College of Engineering (2023), and the ACS OpenEye Outstanding Junior Faculty Award in Computational Chemistry (2022). His research is supported by multiple federal agencies including the National Science Foundation, Department of Energy, Army Research Laboratory, and Office of Naval Research, as well as private corporations and foundations.

• NSF CAREER Award (2023): Supporting research on electrocatalytic nitrate reduction to ammonia
• 1938E Award (2023): Recognizing exceptional mentorship, teaching, and departmental contribution
• ACS OpenEye Award (2022): Honoring outstanding contributions to computational chemistry
• AIChE 35 under 35 Award (2020): In the Energy and Environment category
• Dow Corning Assistant Professorship (2020)

Prof. Goldsmith has mentored an impressive number of students, including two post-doctoral researchers, nine PhD candidates, four master's students, and 19 undergraduate students. His teaching philosophy centers around project-based learning, active lecturing, and inclusive teaching methods. He has developed graduate and undergraduate data science and machine learning courses specifically for engineering students. The Goldsmith Lab is also committed to K-12 outreach and science communication, hosting educational events and contributing to various STEM initiatives.