Uncertainty Quantification of Metal Additive Manufacturing Processing Conditions Through the use of Exascale Computing... Conference Paper November, 2023
DDStore: Distributed Data Store for Scalable Training of Graph Neural Networks on Large Atomistic Modeling Datasets Conference Paper November, 2023
The Kokkos OpenMPTarget Backend: Implementation and Lessons Learned... Conference Paper September, 2023
Uncertainty quantification for computational modelling of laser powder bed fusion Conference Paper May, 2023
A single-tree algorithm to compute the Euclidean minimum spanning tree on GPUs Conference Paper January, 2023
Machine Learning for First Principles Calculations of Material Properties for Ferromagnetic Materials Conference Paper January, 2023
Computational Workflow for Accelerated Molecular Design Using Quantum Chemical Simulations and Deep Learning Models Conference Paper December, 2022
Simurgh: A Framework for Cad-Driven Deep Learning Based X-Ray CT Reconstruction Conference Paper October, 2022
