Inverse Design with Neural Surrogate Models

Par

Vahid Babaei

Max Planck Institute for Informatics

mercredi 8 mars 2023, 10:30-12:00 EST, Salle 3195

Pavillon André-Aisenstadt, Université de Montréal, 2920 Chemin de la Tour

Abstract: The digitalization of manufacturing is turning fabrication hardware into computers. As traditional tools, such as computer aided design, manufacturing, and engineering (CAD/CAM/CAE) lag behind this new paradigm, the field of computational fabrication has recently emerged from computer graphics to address this knowledge gap with a computer-science mindset. Computer graphics is extremely powerful in creating content for the virtual world. The connection is therefore a natural one as the digital fabrication hardware is starving for innovative content. In this talk, I will focus on inverse design, a powerful paradigm of content synthesis for digital fabrication, which creates fabricable designs given the desired performances. Specifically, I will discuss a class of inverse design problems that deals with data-driven neural surrogate models. These surrogates learn and replace a forward process, such as a computationally heavy simulation. I will present a state-of-the-art neural inverse design that addresses the inevitable yet crucial gap between the surrogate and the original forward process by leveraging the uncertainty information. 

Bio: Vahid Babaei leads the AI aided Design and Manufacturing group at the Computer Graphics Department of the Max Planck Institute for Informatics, in Saarbrücken Germany. He was a postdoctoral researcher at the Computational Design and Fabrication Group of Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT. He obtained his PhD in Computer Science from EPFL. Vahid Babaei is a recipient of two postdoctoral fellowships awarded by the Swiss National Science Foundation, and the Hermann Neuhaus Prize of the Max Planck Society. He is interested in developing original computer science methods for both engineering design and advanced manufacturing, and putting these methods into practice in order to create physical products with novel and useful characteristics.