Machine Learning

Integrating Deep Learning with Computational Fluid Dynamics Solvers

The work aims to demonstrate capabilities doing in-situ co-simulations strategies of Machine Learning and Computational Fluid Dynamics Solver (OpenFOAM)

Integrating Data-Driven and High Fidelity Computational Models for Buildings Energy Systems

Residential and commercial buildings account for 41% of total energy consumption in the United States. Optimizing energy consumption and designing more Energy Efficient Green Buildings is a promising approach to reducing energy consumption. Modeling …

Bayesian Neural Networks Distributed Training Performance Analysis at Scale

The aim of the work is to perform distributed training of Bayesian Neural Networks on High Performance Computing Clusters.