Unleashing AI Transformer Models on FPGAs for Accelerating LHC and Particle Physics
This project centers on the deployment of Transformer models for Field Programmable Gate Arrays (FPGA), in order to seamlessly integrate AI capabilities into particle physics expe…
Advanced Peer to Peer Transactive Energy Platform with Predictive Optimization
Applying AI/ML to optimize renewable energy generation and consumption on Smart Grid with block chain technologies
Microsoft Azure Quantum Elements
Accelerate chemistry and materials discovery using AI, HPC, and quantum-ready tools.
Nanoparticle growth kinetics and mechanism
AI is used to digitalize the nanoparticle from TEM images. Morphology and crystalline feature will be made available through AI. Combining with kinetics modeling, AI detects criti…
Center for Mesoscale Transport Properties
Center for Mesoscale Transport Properties
Develop a Machine Learning Framework for Optimal Computational Campaigns for Complex Uncertain Systems
'Two projects to use machine learning to acclerate the design of optimal strategies and robust computational campaigns for complex systems in the presence of substantial data and…
AI/ML in High Energy Physics Research
Within the high energy physics research in the energy, intensity and cosmic frontiers, as well as the advance detector R&D and scientific computing, AI/ML techniques have been dev…
NIF Shot Analytics & Predictive Maintenance Support Pilot
Quick access to specific NIF laser data and problem resolution information
SMMM
AI/ML is being used to evaluate measurements in real-time during simultaneous experiments on two beamlines and then drive subsequent data collection on both of the beamlines to ma…
OpenAI Enterprise
Provide enterprise-grade AI assistance with secure access to OpenAI GPT models.
A Digital Twin for In-silico Spatiotemporally-resolved Experiments
A Digital Twin for In-silico Spatiotemporally-resolved Experiments
Machine learning for accelerated understanding of dynamic catalysis
The understanding of catalytic reactions has been a long-standing challenge due to the complexity and wide range of time scales involved in their mechanisms. There remain signific…
Safeguards Digital Twin
This deals with international safeguars approaches.
Use AI/ML ML to Optimize Data and Experiments at National Synchrotron Light Source II (NSLS-II) and the Accelerator Test Facility (ATF)
Three projects: use ML for denoising in scientific images; use ML to mine large quantities of data for automated evaluation of data quality and predictive analysis; develop AI/ML…
Data-Science Enabled, Robust and Rapid MeV Ultrafast Electron Diffraction System to Characterize Materials Including for Quantum and Energy Applications
Data-Science Enabled, Robust and apid MeV Ultrafast Electron Diffraction System to Characterize Materials Including for Quantum and Energy Applications
Use ML as part of an integrated strategy for forecasting renewable energy resources
This is an inderdisciplinary project aiming to develop a novel system that transforms the forecasting of renewal energy resources by seamlessly integrating a numerical weather pre…
MR-DT
Aid safeguards analysts for determining if a reactor is being used in a non-declared way.
Development of a Planning, Operation, and Control Framework for Hybrid Energy Storage and Renewable Generation Systems
One project: will develop the initial framework for planning, operation, and control of these 'hybrid' energy systems containing high penetrations of renewables together with ener…
Accelerated Nanomaterial Discovery
Historically the discovery and development of new materials has followed an iterative process of synthesis, measurement, and modeling, suitable integration of advanced characteriz…
Google Agentspace / NotebookLM
Unify enterprise data and enable large-scale agent deployment with Google Agentspace.
Use AI/ML for Climate Prediction
Two projects: leverage AI/ML tools to synthesize uncertainty quantification-targeted, complex, multi-scale, multi-domain observations into high-resolution processmodels to charact…
EDX-ClaiMM
Address fundamental knowledge gaps and foster the innovation of new techniques for enhanced characterization and recovery of critical minerals and materials (CMMs) within the US.
Machine Learning for Linac Improved Performance
In Linacs at FNAL and J-PARC, the current emittance optimization procedure is limited to manual adjustments of a few parameters; using a larger number is not practically feasible…
Storage usage effectiveness and data placement optimization at Data Center
The goal of this project is to take data management for data centers to the next level by implementing Artificial Intelligence (AI) and Machine Learning (ML) to create a precise d…