Celia Reina

Celia Reina is an Associate Professor in the Department of Mechanical Engineering and Applied Mechanics at the University of Pennsylvania’s School of Engineering and Applied Science (SEAS). Her research focuses on multiscale modeling of materials, bridging statistical mechanics, thermodynamics, and machine learning. She develops novel frameworks for predicting non-equilibrium material behavior using data-driven methods and uncertainty quantification.

Her work emphasizes integrating computational tools like neural networks (Stat-PINNs, VONNs) with physical principles to model dissipative systems, phase transitions, and mesoscale dynamics. Key areas include coarse-graining techniques, epistemic uncertainty analysis, and predictive modeling of complex materials under dynamic loading.

Recent publications highlight advancements in stochastic systems, resonant metamaterials, and the derivation of thermodynamic models from particle-level fluctuations. She leads efforts in experimental-simulation co-design to enhance predictive capabilities in materials science.