Automated sorting of high repetition rate coherent diffraction data from XFELS
'Coherent X-rays are routinely provided today by the latest Synchrotron and X-ray Free-electron Laser Sources. When these diffract from a crystal containing defects, interference…
Uncertainty Quantification and Instrument Automation to enable next generation cosmological discoveries
This project will develop AI-based tools to enable critical sectors for near-future cosmic applications. Uncertainty quantification is essential for performing discovery science n…
READS: Real-time Edge AI for Distributed Systems
This project will develop and deploy low-latency controls and prediction algorithms at the Fermilab accelerator complex
mass3
GenAI on STEM-optimized LLMs
Simulation-based inference for cosmology
This project will develop and use simulation-based inference to estimate cosmological parameters related to cosmic acceleration in the early and late universe — via the cosmic mic…
Collaborative Machine learning platform for Scientific Discovery
New advances in scientific applied machine learning (ML) offer an opportunity to leverage the commonalities, scientific insights and collected experience of the larger scientific…
Denoising Diffusion to Accelerate Detector Simulation
This program aims to develop generative models for quickly simulating showers of particles in calorimeters for LHC experiments
Tackling Solid-State Electrochemical Interfaces from Structure to Function Utilizing HPC and Machine Learning Tools
Applying AI/ML methods to discover better solid state battery interface material using HPC
5G-enabled Reliable and Decentralized IoT Framework with Blockchain
We propose to develop an end-to-end, 5G-enabled, reliable, and decentralized IoT framework that improves data collection and communication among edge computing devices for science…
Extreme data reduction for the edge
This projects develops AI algorithms and tools for near-sensor data reduction in custom hardware.
Machine Learning for Accelerator Operations Using Big Data Analytics / L-CAPE
Big data analytics for anomaly prediction and classification, enabling automatic mitigation, operational savings, and predictive maintenance of the Fermilab LINAC
AI/ML in Particle Accelerator Controls System
Improving the safety and performance of particle accelerator operations through artificial intelligence assisted control systems.
AI/ML to design and optimize materials and their properties
Design and optimize materials and their properties for Quantum Information Science and clean energy using AI/ML
Intelligent Acquisition and Reconstruction for Hyper-Spectral Tomography Systems
We will develop artificial intelligence (AI) and machine learning (ML) algorithms to enable dramatic improvements in the throughput and performance of hyperspectral (i.e., multipl…
Effects of vehicle traffic on space use and road crossings of caribou in the Arctic [2024 INV#WO0000000110111]
Assessing the effects of industrial development on wildlife is a key objective of managers and conservation practitioners. However, wildlife responses are often only investigated…
AI data harvesting project – ECOSphere [2024 INV#DOI-62]
How can we automate the extraction, classification, and transformation of heterogeneous species-related files (e.g., PDFs, Word docs, Excel sheets, images) uploaded by biologists…
Atlas.ti (Qualitative Data Analysis Software)
Existing software, such as Excel, was insufficient for the increasing quantity of qualitative data collected, necessitating the need for specialized software geared towards qualit…
Water Use Model Development [2024 INV#WO0000000109669]
Estimate multiple categories of water use across the U.S.
Nutrient, Salinity, sediment, temperature, and drought model development
Simulate nutrients (phosphorus and nitrate), temperature, sediment, and salinity in streams across the U.S.
CONUS EcoFlows Planning & Prototype [2024 INV#WO0000000109732]
National-scale ecological-flow response models
Using advanced computing techniques for image-based monitoring [2024 INV#WO0000000109674]
Provide tools and methods for leveraging image-based monitoring and machine learning approaches for measuring surface water properties.
Using advanced computing techniques for mobile monitoring platforms [2024 INV#WO0000000109492]
Support the navigation and swarming capabilities of autonomous vehicle platforms for water monitoring
Water Time-Series Record Automation Framework development
Leverage AI/ML to streamline USGS time-series data processing workflows
Invasive Carp Harvest Predictive Model
identify where invasive carp are congregating in large numbers in the Mississippi River for targeted harvest