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 Principal Investigator Project Type Project Status
Active Learning for Rapid Design of Vaccines and Antibodies 20-ERD-032 Thomas Desautels Exploratory Research Final
Approximate High-Performance Computing: A Fast and Energy-Efficient Computing Paradigm in the Post-Moore Era 20-ERD-043 Harshitha Menon Gopalakrishnan Menon Exploratory Research Final
Probabilistic Models for Dynamic Hypergraphs with Content 20-ERD-049 Grant Boquet Exploratory Research Final
Scientific Machine Learning at Extreme Scale: Optimal Control for Deep Learning in High-Performance Computing 21-ERD-051 Stefanie Guenther Exploratory Research Final
Learning a Nonlinear Solver Optimized to Solve the Problem of Electron Density and Effective Atomic Number Reconstruction 21-FS-013 Kadri Aditya Mohan Feasibility Study Final
Efficient High-Frequency Time-Harmonic Wave Propagation Solvers Using Discontinuous Petrov-Galerkin Methods 22-FS-009 Socratis Petrides Feasibility Study Final
Zeroth-Order Machine Learning for Flexible Integration of Domain Knowledge 22-FS-019 James Diffenderfer Feasibility Study Final
Virtual Inspections: Fast and Intuitive Inspections of Manufactured Parts in Virtual Reality 22-FS-026 Haichao Miao Feasibility Study Final
Hierarchical, Multimodel, Multiscale Parallel-In-Time 22-FS-029 Paul Tranquilli Feasibility Study Final
Deep Facial Representation for Quantification of Emotion Dynamics 22-FS-032 Piyush Karande Feasibility Study Final
Decentralized Autonomous Networks for Cooperative Estimation 20-SI-005 Ryan Goldhahn Strategic Initiative Final
Hypothesis Testing via Artificial Intelligence: Generating Physically Interpretable Models of Scientific Data with Machine Learning 19-DR-003 Brenden Petersen Disruptive Research Final
Beating Monte Carlo: The Polynomial Method in Lattice Problems 19-DR-013 Christian Scullard Disruptive Research Final
Optimal High-Order Solvers 20-ERD-002 Will Pazner Exploratory Research Final
Safe and Trustworthy Machine Learning 20-ERD-014 Bhavya Kailkhura Exploratory Research Final
Modeling Complex Behavior of Lattices to Enable Multiscale Design 20-ERD-020 Seth Watts Exploratory Research Final
Knowledge-Driven Machine Learning 21-ERD-012 Jayaraman Jayaraman Thiagarajan Exploratory Research Continuing
Achieving Peak Performance of High-Performance Computing Applications by Optimizing Parallelism Compilation 21-ERD-018 Giorgis Georgakoudis Exploratory Research Continuing
Interactive Exploratory Graph-Enabled Data Analytics at High-Performance Computing Scales 21-ERD-020 Roger Pearce Exploratory Research Continuing
Cross-Scale Modeling for Component Scale Simulations 21-ERD-022 Matthew Nelms Exploratory Research Continuing