Simone Peter

Simone Peter, a graduate student in computational science and engineering, is reimagining the design of concrete buildings to significantly reduce their embodied carbon footprint. Her research combines structural mechanics, optimization theory, and machine learning to explore new, buildable geometries that utilize less material without compromising performance. As a MathWorks Fellow, Simone will expand her topology and shape-optimization framework by incorporating symbolic computation and automatic differentiation to customize reinforced-concrete manufacturability constraints and train AI models that accelerate the prediction of efficient slab designs. She has already implemented a simulation and optimization pipeline that evaluates and improves beam–slab networks, incorporating structural logic and manufacturing constraints to guide practical outcomes. By leveraging MATLAB’s unique integration of symbolic computation, numerical solvers, and AI tools, Simone is creating a scalable, multi-component design methodology. Her work could revolutionize sustainable building design, providing engineers with powerful new tools to reduce emissions at the structural level.