Pranav Bahl

Biography

Pranav Bahl is currently a master’s student at the University of Michigan, Ann Arbor where he is exploring Denoising diffusion probabilistic models (DDPMs) and latent diffusion models utilizing tensor network latent spaces and is involved with multiphysics simulations of Reactor Pressure Vessels (RPVs) at the AIMS Lab. Previously he completed his master’s degree from the Dept. of Aeronautics, Imperial College London (ICL) in concentration Advanced Computational Methods for Aeronautics, Fluid mechanics and Fluid-structure interaction. At Imperial, he primarily explored autonomous data-driven chaotic dynamical systems utilizing classical and quantum recurrent neural networks. His graduate level courseworks ranged from Turbulence/Turbulence modeling, Multidisciplinary Optimization, Computational fluid dynamics (CFD) to Machine learning/Artificial intelligence, Linear systems theory and Computational linear algebra. He completed his bachelor’s from the Dept. of Mechanical Engineering, Delhi Technological University (DTU). During his bachelor’s degree he was primarily interested in exploring Deep learning based Reduced order models (ROMs) for large scale, physics-based high-fidelity simulations either for autonomous evolution of discretized PDEs or for the state-estimation problems.