Projects/Programs

Displaying 1 - 25 of 55

Adaptive Closed-Box Interference Susceptibility Testing

Ongoing

Our approach combines state-of-the-art testbed automation, RF metrology, data analytics, and machine learning to develop flexible, broad-purpose methods that will enable efficient, rigorous testing. Specifically, we plan to establish methods for experimental characterization of closed-box

AI-based measurements For Imaging

Ongoing

The problem addressed in this work lies in enabling scientists to apply artificial intelligence (AI) based models to deriving measurements from terabyte-sized images. This problem is important as image-based measurements can become more accurate by introducing supervised AI-based models instead of

Artificial Intelligence for Chemical Manufacturing

Ongoing

The chemical manufacturing design process relies heavily on the recommended values that engineers and researchers usually obtain from handbooks and databases. Those sources often lack easy ways to judge the reliability of information, either in the sense of where the data come from or what the

Augmented Intelligence for Manufacturing Systems (AIMS)

Ongoing

Objective To overcome existing measurement challenges via augmented intelligence, the fusion of integrated metrology, physics-based models, and artificial intelligence, to enable monitoring, diagnostics, and prognostics of manufacturing systems and their processes. Technical Idea One research

Autonomous Systems Assurance

Ongoing

Achieving assured autonomy in any environment requires methods for measuring the input space, to show that the test environment adequately covers real-world conditions that may be encountered. Although some statistical and structural coverage metrics are relevant, they are terribly inadequate for

Biosecurity for Synthetic Nucleic Acid Sequences

Ongoing

Emerging biotechnology, enabled by the ability to genetically engineer biological systems similar to the way we write software and program computers, can provide solutions to many pressing societal needs related to health, food security, supply chain resilience, and job growth for economic and

Broadband Coherent Anti-Stokes Raman Scattering (BCARS) Microscopy

Ongoing

Impact There is a need for label-free chemical microscopy in medicine, biology and materials science. Most of the current methods use chemical labels that often disturb the distribution and nature of chemical components being investigated. The method we are developing enables noninvasive and rapid

CHiMaD Phase Field Community

Ongoing

Please see the community website, https://pages.nist.gov/chimad-phase-field/

Classification of 3.5 GHz Spectrograms

Completed

This project compared various detection algorithms for federal incumbent radar signals in the 3550-3650 MHz band using a set of over 14,000 spectrograms collected by the completed Waveform Measurements of Radars Operating in the 3.5 GHz Band project. The results demonstrated that training deep

Classification Methods for the NIST Biorepository

Ongoing

NIST has been archiving biological and environmental specimens, including marine animal and environmental samples, for over 40 years. Currently, these biospecimens are stored at cryogenic temperatures in the NIST Biorepository located at the Hollings Marine Laboratory in Charleston, SC. Various

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Computation Platform for AI/ML

Ongoing

In collaboration with NIST’s Information Technology Laboratory and Office of Information Systems Management, the Office of Data and Informatics is supporting the deployment and development of the long-term operational model for the enki computation platform for NIST staff members who research and

Consistency Analysis and Uncertainty in ‘omic Data

Ongoing

‘Omics is increasingly moving out of the laboratory and towards use in industrial and commercial applications. For instance, in biomanufacturing, there is a need for quality control when developing biotherapeutics, which will almost certainly require a machine-learning classifier to separate

Data Driven Decision Support for Additive Manufacturing

Completed

Objective To develop and deploy the metrics, models, and best practices for using product definition, advanced analytics, and machine learning methods in additive manufacturing design and process planning to reduce lead times and support first-part-correct goals. Technical Idea Future advancements

AI/ML for Data Extraction and Uncertainty Predictions

Ongoing

The Material Measurement Lab at NIST employs artificial intelligence for the prediction and discovery of materials characteristics. Our applications of artificial intelligence (AI) accelerate materials research as well as help the community learn about AI's capabilities and gain confidence in

Deducing Prior Material Deformation from Simple Mechanics

Ongoing

Process-structure-property linkages suggest an opportunity to deduce processing from behavior. Simple imaging experiments provide rich sources of data. Can we deduce prior deformation? Scheme: Thin film plasticity Deform to some reference strain Unload Deform to test strain, image Deduce

Deep Generative Modeling for Communication Systems Testing and Data Sharing

Completed

After initial investigations with simulated datasets, we plan to develop generative models using real datasets. Potential applications of this work include generation of waveforms for interference testing, characterization of closed-box communication systems, and signal obfuscation for data sharing

Deep Learning for MRI Reconstruction and Analysis

Ongoing

The project is proceeding in three directions. Creating a new MRI reference artifact designed to assess geometric distortion using NIST’s MRI scanner. The artifact will be small enough to fit within the scanner with sufficient clearance to allow for variation in positioning within the scanner.

Edge AI

Ongoing

This project: Develops edge learning and edge-enabled collaborative learning algorithms. Develops measurement methods for testing the performance and robustness of edge-learned, and more generally collaboratively learned, AI/ML models. Collaborates with other projects (e.g., 5G/6G Core Network

Embodied AI and Data Generation for Manufacturing Robotics

Ongoing

Objective To facilitate the adoption of AI-based robotic approaches in practical manufacturing scenarios by creating test methods that target AI-enabled robotic systems, evaluating the performance of AI-enabled robotic systems, and creating manufacturing-relevant and AI-centric datasets. Technical

Emerging Hardware for Artificial Intelligence

Ongoing

Here is a brief description of our work with links to recent papers from our investigations, broadly classified as experimental and modeling. A brief overview of Josephson junction-based bio-inspired computing can be found in our review article. Experimental We have facilities to develop our devices

Explainable Artificial Intelligence Based Modeling Applied to OMICS Problems

Ongoing

The goal of the project is to produce billions of certified values from multiple measurement methods with well-characterized uncertainty in the “’omics” field (genomics, proteomics, transcriptomics). These values are prepared by a joint effort between human experts and trained AI based models for

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Gene Delivery Particle Analysis with High-Throughput Light Scattering Microscopy

Ongoing

This project aims to develop light-scattering microscopy methods for rapid, multi-attribute characterization of gene therapy particles at the single particle level. Emerging gene therapy treatments use gene delivery particles, such as viral vectors and non-viral carriers, to cure intractable

Genome in a Bottle

Ongoing

Consortium goals: The Genome in a Bottle Consortium is a public-private-academic consortium hosted by NIST to develop the technical infrastructure (reference standards, reference methods, and reference data) to enable translation of whole human genome sequencing to clinical practice and innovations

High Performance Crystal Plasticity

Ongoing

“Crystal plasticity” is a computationally intensive way of computing the behavior of materials undergoing large permanent deformations. Computation is very inhomogeneous: A large effort is expended everywhere, but only a small portion of the computational domain is doing anything interesting. We

Identification, Suitability Testing, and Property Determination from Untargeted Measurements

Ongoing

In many applications, detailed knowledge of a fluid mixture’s physical behavior is needed. This can include physical properties such as viscosity and qualitative properties such as solubility. For instance, a dissolved polymer may suddenly precipitate out of solution when exposed to saline, and if

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