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Information Technology

Artificial intelligence

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Physics and Hardware for Intelligence

Ongoing

Our work in this area can be separated into two categories: conceptual and experimental. Please read our publications linked below for more information. Experimental: Our latest generation of synaptic circuits are described in a 2024 paper published in APL Machine Learning. These circuits are our

AI self-quality assurance using learning curves in feedback loops

Ongoing

One application of artificial intelligence (AI) in materials is the acceleration of materials innovation, which is the mission of the Materials Genome Initiative. However, to decrease the cost and time-to-market, we must continuously assess the quality of models with new facts. AI quality assurance

Semi-Automatic Curation

Ongoing

Scientific literature is undeniably an important source of scientific data for research but the review and curation of data from literature is both tedious and time consuming. Investigators must sort through many articles to review and extract relevant information. For many areas of research

Fig. 1. Die containing 285 superparamagnetic tunnel junctions.

Spintronics for Neuromorphic Computing

Ongoing

Magnetic tunnel junctions (see Fig. 1) consist of two thin films of ferromagnetic material separated by a few atomic layers of an insulating material. The insulator is so thin that electrons can tunnel quantum mechanically through it. The rate at which the electrons tunnel is affected by the

This figure shows a microscopic image of a field of cells, some of which are pseudocolored red to indicate that these cells remain pluripotent.

Stem Cell Metrology: WSDOM

Ongoing

Stem cells are critical starting materials for advanced therapies and diagnostic devices. The most commonly used are induced pluripotent stem cells (iPSCs) which can be created with any individual’s skin cells, and then can be coaxed to become cells for any tissue of the body. Therapies and

Subspace-Informed Deep Learning Solutions for Nanoscale Microscopy

Ongoing

Cutting-edge nanoscale microscopy techniques such as near-field scanning microwave microscopy (NSMM) and atom probe tomography (APT) enable a multi-dimensional virtual representation of an artifact to be constructed from a set of experimental measurements. These imaging techniques, which are

Synthetic Biology

Ongoing

New measurement methods and tools are required for biology to emerge fully as an enabling, practical platform for engineering. The Cellular Engineering Group works to provide a foundation of measurement assurance to support the control and rational design of biological function. Through state of the

Teaching Liquid State Theory to an Artificial Neural Network (ANN)

Ongoing

Scientific questions: Can an ANN allow us to predict the structure of fluids that are impossible to predict numerically via liquid-state theory? Can we learn something about liquid-state theory itself by the nature of the trained ANN? What features do the hidden layers capture?

Fig. 1. Time re-Envisioned: Not a biproduct of computation but the domain in which information is encoded. Leads to different mathematical functions becoming energy efficient primitives.

Temporal Computing

Ongoing

In standard integrated circuits, information that is coded as ones and zeros is implemented by voltages on wires being high or low. The circuits consume energy during transitions between these voltages. Binary numbers have a voltage per bit so there are a lot of transitions each time a number

Training and optimization of hardware neural networks

Ongoing

The goal of this project is to develop a general method that can train many different types of neural networks, and to demonstrate and evaluate their performance on new emerging hardware. We aim to develop and demonstrate training on diverse hardware platforms, and in the presence of realistic noise

Trusted AI framework for a new class of Standard Reference Materials and Data with exquisitely characterized uncertainty for billions of properties

Ongoing

The measurement of diverse molecular classes in biospecimens containing millions of molecules, known as omics, is increasingly important in the life sciences and medicine, and used to find novel cancer therapeutics, discover COVID-19 infection pathways, and diagnose diseases. NIST RMs and SRDs for

Trustworthy Intelligent Networks

Ongoing

Our current research efforts include: The application of AI/ML techniques to detect abuse of the Domain Name System (DNS). The development of measurement techniques to characterize the robustness of AI/ML approaches to botnet detection. The application of AI/ML techniques to detect anomalies in the

AI User Trust

Ongoing

The Visualization and Usability Group’s AI User Trust project provided foundational work for our new AI User Trust Measurement research, and continues to inform our larger Human-Centered AI program. Please read more about our current work on those pages. The information that follows is maintained

Using AI to Determine Structure-Property Relations in Materials

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

Validating A.I. Pipelines for Analysis of Live Cell Image Data

Ongoing

We are exploring methods for very high-speed cell image data collection, which is enabling the repeated sampling of thousands of cells every 2 minutes. Rapid sampling allow us to observe dynamic processes in cells (such as cell division) on a relevant time scale. Such rates of sampling allows us to

Wireless Coexistence

Ongoing

What is Wireless Coexistence? Wireless coexistence is the capability of multiple wireless devices and services in the same geographical area to access the same RF spectrum band simultaneously without causing harmful interference to each other. In other words, can they all operate successfully and

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