Raphaël
Pestourie
Assistant Professor, School of Computational Science & Engineering
Raphaël Pestourie earned his Ph.D. in Applied Mathematics and an AM in Statistics from Harvard University in 2020. Prior to Georgia Tech, he was a postdoctoral associate at MIT Mathematics, where he worked closely with the MIT-IBM Watson AI Lab. Raphaël’s research focuses on scientific machine learning at the intersection of applied mathematics and machine learning and inverse design via scientific machine learning and large-scale electromagnetic design.
Research Interests
The goal of my group is to extend the horizon of accurate models for the optimization of engineering solutions. For example, we introduce models where trial and error and heuristics are the state of the art for practitioners. We formulate engineering questions as computational optimization problems and develop techniques to find optimal answers with an efficient combination of data and computing resources. To that end, my group develops fast approximate PDE models and scientific machine learning models that combine AI (Artificial Intelligence) models and scientific models, end to end. These new models enable the ressource-efficient and large-scale optimization of engineering solutions.