Bio: Celia Reina is an Associate Professor in Mechanical Engineering and Applied Mechanics at the University of Pennsylvania. She joined in 2014 after holding the Lawrence Postdoctoral Fellowship at Lawrence Livermore National Laboratory and the HCM postdoctoral Fellowship at the Hausdorff Center of Mathematics in Bonn, Germany. Dr. Reina received her PhD from the California Institute of Technology in Aerospace Engineering in 2011, following a B.S. in Mechanical Engineering from the University of Seville in Spain, and a Master in Structural Dynamics from Ecole Centrale Paris in France. She is a recipient of the Eshelby Mechanics Award for Young Faculty (2017) and the NSF CAREER Award (2021).

Abstract: The fascinating diversity of material behavior at the macroscopic scale, including plasticity, phase transformations, viscoelasticity or diffusion, can only emerge from the underlying atomistic or particle behavior. Yet, the direct connection between these two scales for non-equilibrium phenomena remains an extremely challenging quest from both a theoretical and computational perspective. This knowledge gap currently hinders predictive simulations and material discovery, and leads to large economic losses and barriers to innovation in many industrial sectors. In this talk, we will discuss several advances in the predictive modeling of non-equilibrium mechanics, by combining tools from continuum mechanics, statistical physics, applied mathematics, as well as machine learning and data-driven strategies.