A variational condition for minimal-residual latent representations
- ICLR 2023
Eloisa Bentivegna is a Research Staff Member in Daresbury, UK. She holds a PhD in Physics, with a minor in High Performance Computing, from Penn State University, and has served as a postdoctoral scholar at the Center for Computational and Technology (USA), a Marie Curie Fellow at the Max Planck Institute for Gravitational Physics (Germany), as well as a National Montalcini Fellow and faculty member of the Physics Department at the University of Catania (Italy) before joining IBM. She has vast experience in the application of computational techniques to the frontiers of theoretical physics, most notably strong gravity and high-energy quantum fields.
She currently works on building computational models of fluid-dynamical systems and developing an infrastructure for verifying and streamlining these models using cognitive technologies. Her broader expertise involves multiscale phenomena and coarse graining, relativistic optics, and nonlinear elliptic problems. She is an author of and contributor to a number of modules in the Einstein Toolkit, the main community code infrastructure in Numerical Relativity, and keeps an active interest in Classical and Quantum Gravity and Cosmology. She is a currently a UKRI Future Leaders Fellow.