2020 Fellow

Jacques Esterhuizen is a fourth-year Ph.D. candidate in the Department of Chemical Engineering and works in the Goldsmith and Linic Research Groups. His research focuses on using machine learning to augment and improve current data-driven/computational approaches to studying heterogeneous catalysts, which rely heavily on resource-intensive quantum mechanical modeling typically performed on high-performance supercomputers. The models and strategies developed in his work will accelerate and automate the discovery of catalytic trends for industrially relevant catalytic systems and catalysts for emerging technologies such as fuel cells, energy storage, and solar fuels.