High-Performance Computing Simulation and Data Science - 2021

Project Title	Project Code	Principal Investigator	Project Type	Project Status
Scientific Machine Learning at Extreme Scale: Optimal Control for Deep Learning in High-Performance Computing	21-ERD-051	Stefanie Guenther	Exploratory Research	Continuing
Modeling Complex Behavior of Lattices to Enable Multiscale Design	20-ERD-020	Seth Watts	Exploratory Research	Continuing
Decentralized Autonomous Networks for Cooperative Estimation	20-SI-005	Ryan Goldhahn	Strategic Initiative	Continuing
Robust Control of Scientific Simulations with Deep Reinforcement Learning	21-SI-001	Daniel Faissol	Strategic Initiative	Continuing
Automated Software Integration	21-SI-005	George Todd Gamblin	Strategic Initiative	Continuing
MADSTARE: Modeling and Analysis for Data-Starved or Ambiguous Environments	19-SI-004	Michael Schneider	Strategic Initiative	Final
Machine Learning-Driven Dynamic Four-Dimensional X-Ray Computed Tomography Reconstruction	20-FS-010	Hyojin Kim	Feasibility Study	Final
Reliable Linear Solvers in Unreliable Computing Environments	21-FS-007	Christopher Vogl	Feasibility Study	Final
The Applicability of Unit Systems to High-Performance Computing Applications	21-FS-016	Tristan Vanderbruggen	Feasibility Study	Final
Scalable Motif-Driven Parallel Generative Adversarial Net for Community Detection	21-FS-029	Byung Yoo	Feasibility Study	Final
Using a Compressed Format for Floating-Point Data as a Data Type to Create Adaptive-Precision Compressed Arrays	21-FS-028	Alyson Fox	Feasibility Study	Final
Efficient Reduced-Order Models for Multi-Physics Simulations	21-FS-042	Youngsoo Choi	Feasibility Study	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	Continuing