Parthenon: a flexible framework for rapid development of performance portable multiphysics codes
When big neural networks are not enough: physics, multi-fidelity and kernels
Alexander Coppeans (Aerospace Engineering): Aerodynamic Shape Optimization with Curved Mesh Adaptation
Heaviside Composite Optimization, a new paradigm of optimization
Liuyun Xu (Civil Engineering): Adaptive Deep Learning-Powered Multi-fidelity Stratified Sampling for Efficient Failure Analysis of Nonlinear Dynamic Systems
Jasmin Lim (Aerospace Engineering): A Hybrid Surrogate Modeling Framework for Digital Twins of Nuclear Energy Systems
Identifying coherent structures and controlling turbulent flows through deep learning
Baudouin Fonkwa Kamga (Mechanical Engineering): Numerical simulation of the collapse of a cavitation bubble near a deformable solid surface
Xinhai Hou (Bioinformatics): Scalable foundation model training for computational pathology
From Turbulent Flows to Video Games: Managing Large-Scale Data with Tensor Decomposition