26 Federal contracts awarded since 2019

Detects and classifies small uncrewed aircraft from hyperspectral imagery, using spectral signature rather than shape, so targets that defeat conventional optical tracking are still resolved.

Identifies concealed contraband by spectral signature at ports of entry, with on-sensor neuromorphic inference so screening runs at the speed of the queue.

An imaging instrument that measures temperature across a surface from its emitted spectrum, used to characterize the heat shields of hypersonic vehicles under test.

An uncrewed aircraft carrying several sensors that surveys structures for corrosion, replacing slow and costly manual inspection.

An automated screening campaign that searches high-entropy alloy compositions for high-temperature strength and oxidation resistance together, narrowing a very large candidate space down to a shortlist worth making and testing.

Recovers gold, copper and other constituents of value from electronic waste electrochemically and at room temperature. 25% higher recovery, 75% less chemical reagent, 30% lower water and electrical cost, and no toxic emissions. Commercialized as E-RECOV.

A curated database and learned models relating composite formulation to flammability, so candidate materials can be screened before they are manufactured and burned.

Engineered metamaterial surfaces on micromirror arrays that steer and shape infrared beams without moving bulk optics, reducing the size, weight and power of the assembly.

A sensor that performs part of the recognition task in the optics themselves, using metamaterial elements, so less computation is required downstream of the focal plane.

Automatic target recognition that uses metamaterial optics to do part of the detection in the lens itself, cutting the processing needed behind the sensor.

Modeling tools for evaluating store separation from an aircraft, replacing part of a test campaign that is otherwise flown.

Machine-learning models that forecast emissions from amine-based carbon capture, helping plants stay within environmental limits.

A scalable, user-friendly computing platform for power plant reliability and maintenance software, built with a national laboratory.

AI that reads source code the way a reviewer does and flags the vulnerabilities an attacker could reach, before the code is fielded.

Real-time detection of cyber threats on high-performance computing networks, with neuromorphic hardware keeping pace with the traffic.

Machine-learning detection of cyber threats on defense networks, spotting traffic that departs from normal behavior as it happens.

A simulator that generates synthetic aperture radar imagery in real time, so detection and classification models can be trained and evaluated against scenarios that are impractical or too expensive to fly.

Surveys the radio-frequency environment to detect and locate signals already in the air, so they can be used for sensing and navigation.

Methods for establishing that a trained model behaves within specification before it is fielded, addressing the assurance gap that keeps machine learning out of safety-critical defense systems.

Carries verification and validation methods forward to models in fielded defense systems, so their behavior can be trusted in operation.

Detection and tracking of hypersonic threats from ground-based sensors, with inference on neuromorphic hardware to hold the latency budget that the closing speeds demand.

Fuses several dissimilar sensors into a single track picture, holding identity across handoffs where any individual sensor loses the object.