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Advancing the state of the art in measurements of sound, vibration, force, acceleration and velocity
information into neural networks for modeling dynamic systems; use of uncertainty information to improve the performance of sensor-network based measurements employing machine learning; uncertainty
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303.497.3665 Karl Francis Stupic [email protected] 303.497.4564 Description Neural net systems have been developed to process magnetic resonance imaging (MRI) data from sensor space into real space and
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are developing machine learning-driven autonomous metrology research systems, with the goal of accelerating the development of self-correcting photonic and quantum sensor networks. These systems combine machine
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inertial navigation, medical imaging, and all-optical sensor networks. We are also interested in integrated cavity optomechanical devices that have sufficiently low optical and mechanical loss
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RAP opportunity at National Institute of Standards and Technology NIST Indoor Localization and Tracking Location Information Technology Laboratory, Advanced Network Technologies Division
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networks. Expert Systems with Applications, 223, p.119899. Large Language Models (LLMs); Recommendation Systems; Interpretable Deep Learning; Real-Time Decision Support; Wearable Sensors; Fireground
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Sensor Science Division in Gaithersburg, MD. In Boulder, opportunities in JNT system research include ultra-low noise system design, SFQ electronics, electromagnetic interference (EMI) rejection/correction