High-Performance Computing Simulation and Data Science

Project Highlights

 
FY2022

Click on any of the project titles below to view a brief project summary,
or return to our Project Highlights page to view lists of FY22 projects in other research categories.

Project Title Project Code Project Type Project Status
Scientific Machine Learning at Extreme Scale: Optimal Control for Deep Learning in High-Performance Computing 21-ERD-051 Exploratory Research Final
Learning a Nonlinear Solver Optimized to Solve the Problem of Electron Density and Effective Atomic Number Reconstruction 21-FS-013 Feasibility Study Final
Efficient High-Frequency Time-Harmonic Wave Propagation Solvers Using Discontinuous Petrov-Galerkin Methods 22-FS-009 Feasibility Study Final
Zeroth-Order Machine Learning for Flexible Integration of Domain Knowledge 22-FS-019 Feasibility Study Final
Virtual Inspections: Fast and Intuitive Inspections of Manufactured Parts in Virtual Reality 22-FS-026 Feasibility Study Final
Hierarchical, Multimodel, Multiscale Parallel-In-Time 22-FS-029 Feasibility Study Final
Deep Facial Representation for Quantification of Emotion Dynamics 22-FS-032 Feasibility Study Final
Decentralized Autonomous Networks for Cooperative Estimation 20-SI-005 Strategic Initiative Final
Hypothesis Testing via Artificial Intelligence: Generating Physically Interpretable Models of Scientific Data with Machine Learning 19-DR-003 Disruptive Research Final
Beating Monte Carlo: The Polynomial Method in Lattice Problems 19-DR-013 Disruptive Research Final
Optimal High-Order Solvers 20-ERD-002 Exploratory Research Final
Safe and Trustworthy Machine Learning 20-ERD-014 Exploratory Research Final
Modeling Complex Behavior of Lattices to Enable Multiscale Design 20-ERD-020 Exploratory Research Final
Active Learning for Rapid Design of Vaccines and Antibodies 20-ERD-032 Exploratory Research Final
Approximate High-Performance Computing: A Fast and Energy-Efficient Computing Paradigm in the Post-Moore Era 20-ERD-043 Exploratory Research Final
Probabilistic Models for Dynamic Hypergraphs with Content 20-ERD-049 Exploratory Research Final
Improving Extrapolation Behavior in Deep Neural Networks 22-ERD-006 Exploratory Research Continuing
Adaptive Sampling for Risk-Averse Design and Optimization 22-ERD-009 Exploratory Research Continuing
Large-Scale Shape Optimization with Conformal Meshes 22-ERD-023 Exploratory Research Continuing
Next-Generation Implicit Neural Representation for Ill-Posed and Dynamic Computed Tomography Reconstruction 22-ERD-032 Exploratory Research Continuing