Major programs running with the Navy, the Air Force, DARPA, the Missile Defense Agency, Homeland Security and the Department of Energy, alongside Lockheed Martin and the national laboratories.
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. Commercialised 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.
The programme CyberNeuro-RT came out of. A hybrid supervised and unsupervised deep learning ensemble for network intrusion detection, ported to neuromorphic silicon so inference runs at a fraction of the power a GPU needs.
Static and learned analysis of source repositories to surface exploitable defects before code ships, trained against mission-critical codebases. Commercialised as CNRT CodeLens.
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.
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.
Fuses several dissimilar sensors into a single track picture, holding identity across handoffs where any individual sensor loses the object.
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.
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 defence systems.
Modelling tools for evaluating store separation from an aircraft, replacing part of a test campaign that is otherwise flown.
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.
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