Robert M. Kirby

Using residual analysis to characterize and control the impact of noisy data on stress intensity factor models from machine learning

Efficiently training SciML models with derivative-informed training data using order truncated imaginary numbers

Using residual analysis to characterize and control the impact of noisy data on stress intensity factor models from machine learning

Tradeoffs in automated financial regulation of decentralized finance due to limits on mutable turing machines.

Stress intensity factor models using mechanics-guided decomposition and symbolic regression

Stress intensity factor models using mechanics-guided decomposition and symbolic regression

Algorithm 1041: HiPPIS—A High-order Positivity-preserving Mapping Software for Structured Meshes

Kolmogorov n-widths for multitask physics-informed machine learning (PIML) methods: Towards robust metrics.

A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions

Deep neural operators as accurate surrogates for shape optimization

A metalearning approach for Physics-Informed Neural Networks (PINNs): Application to parameterized PDEs

Multi-Omic Integration of Blood-Based Tumor-Associated Genomic and Lipidomic Profiles Using Machine Learning Models in Metastatic Prostate Cancer.

Particle Merging-and-Splitting.

Robust topology optimization with low rank approximation using artificial neural networks

Residual Gaussian process: A tractable nonparametric Bayesian emulator for multi-fidelity simulations

Vector Field Decompositions Using Multiscale Poisson Kernel.

Image-Based Multiresolution Topology Optimization Using Deep Disjunctive Normal Shape Model

The Effect of Data Transformations on Scalar Field Topological Analysis of High-Order FEM Solutions.

Nektar++: Enhancing the capability and application of high-fidelity spectral/hp element methods

Parametric topology optimization with multiresolution finite element models

Scalable High-Order Gaussian Process Regression

RBF-LOI: Augmenting Radial Basis Functions (RBFs) with Least Orthogonal Interpolation (LOI) for solving PDEs on surfaces

Optimization of Large-Scale Vogel Spiral Arrays of Plasmonic Nanoparticles

Visualization in Meteorology—A Survey of Techniques and Tools for Data Analysis Tasks

Multi-Dimensional Filtering: Reducing the Dimension Through Rotation

Hexagonal Smoothness-Increasing Accuracy-Conserving Filtering

Optimising the performance of the spectral/<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si10.gif" display="inline" overflow="scroll"><mml:mi>h</mml:mi><mml:mi>p</mml:mi></mml:math> element method with collective linear algebra operations

Nektar++: An open-source spectral/ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si20.gif" display="inline" overflow="scroll"> <mml:mi>h</mml:mi> <mml:mi>p</mml:mi> </mml:math> element framework

To CG or to HDG: A Comparative Study in 3D

Inverse Design of Metal Nanoparticles’ Morphology

Collaborative Research: MATH-DT: Computationally efficient hypercomplex variable-based sensitivity methods for rapid Digital Twin model updating

Elements: High-performance simulation of time-dependent problems via domain-specific languages

Collaborative Research: High-order approximation of variational inequalities and bounds-constrained partial differential equations

SHF: Small: Collaborative Research: Transform-to-Perform: Languages, Algorithms, and Solvers for Nonlocal Operators

Collaborative Research: Transforming Serendipity Elements from Theory to Practice

Collaborative Research: Multiphysics modeling and analysis of thermo-visco-acoustic equations with applications to the design of trace gas sensors

The Best of Both: Toward a hybrid discrete and continuum multiscale platelet aggregation and coagulation model

Small: Collaborative Research: Transform-to-Perform: Languages, Algorithms, and Code Transformations for High-Performance FEM

SI2-SSE: A GPU-Enabled Toolbox for Solving Hamilton-Jacobi and Level Set Equations on Unstructured Meshes

AF: Small: Metanumerical Computing for Emerging Architectures: Automated Embedded Algorithms for Partial Differential Equations on Multicore Platforms

AF: Small: Metanumerical Computing for Emerging Architectures: Automated Embedded Algorithms for Partial Differential Equations on Multicore Platforms

GV: Small: Collaborative Research: Analysis and Visualization of Stochastic Simulation Solutions

Automated Intrusive Algorithms for Numerical Simulation of Partial Differential Equations via Software-Based Frechet Differentiation

CAREER: Quantifying and Controlling Error and Uncertainty in Computational Inverse Problems