Advanced computing research supporting scientific discovery, spanning high-performance computing systems, AI and large-scale data analysis, scientific visualization, immersive computing, and emerging computing architectures.
Applies predictive AI models, reinforcement learning, and human-in-the-loop simulation to coordinate a facility's heterogeneous computing resources as a unified pool for a broad spectrum of applications.
A education focused program to train physics and computer science students in the computational tools necessary to advance the particle physics field.
Provides hands-on educational modules in data systems, enhancing data proficiency across students and professionals through practical exercises and cloud integration, aiming to bolster innovation leadership.
Utilizing tele-robotic and eventually tele-autonomous operations with digital twins, to enhance virtual interaction and control.
A national workshop convening academia, industry, and government to define the software infrastructure needed for an accessible, trustworthy national AI research resource.
This project creates a national-scale testbed for artificial intelligence research, connecting AI-enabled devices and environmental sensors across the U.S. to study Earth's climate and biosphere while training a diverse AI-skilled scientific workforce.
Sage is reusable cyberinfrastructure providing climate, traffic, and ecosystem scientists new data for building models to study coupled systems. The software and hardware components developed in Sage will be open-source and provide an open architecture to enable scientists from a range of fields to build their own intelligent sensor networks.