Suyong Kim is a PhD candidate whose research applies optical diagnostics and computational modeling techniques in the fields of energy materials and energy sustainability. As a MathWorks Fellow, Suyong will pursue two primary projects. The first focuses on modeling the combustion of metal fuels as a promising candidate of carbon-neutral energy source. His second project aims at creating a practitioner design tool for an improved charcoal-fired cookstove to protect the health of people who use inefficient and highly polluting products for cooking, space heating, and food preservation. Suyong uses MATLAB to develop a new data-driven framework that derives chemical kinetic mechanisms and transport properties of solid fuels based on optical diagnostics. He also builds a reduced-order model to guide the design of metal fuels and improved cookstoves. Such an image-based modeling framework and reduced order model could be generalized to many other applications such as medicine modeling and chemical looping.