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Field
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perception pipelines, including BIM-based SLAM, traversability map analysis, and 3D LiDAR/vision sensor fusion. • Design few-shot learning algorithms for robust detection of temporary construction objects
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capabilities comprising vehicle-mounted sensors, drone operations, on/off-road robotics, high-precision geo-localisation, bio-signal data collection, X-ray security scanning, virtual reality and on-demand wide
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estimation algorithms that operate reliably in challenging environments (e.g., low texture, illumination variation, dynamic scenes, or sensor degradation). The research will integrate model-based estimation
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Wideband Antenna Arrays is performed. The tasks associated with this project involve, but are not limited to, Sensor node hardware design and antenna evaluation RFSoC-based multichannel acquisition and
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top setup prototyping the translation of dynamic quantum algorithms such as double-bracket algorithmic cooling to applications in quantum sensing using NV centers. With whom? With Prof. Marek Gluza
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underground, where cameras and conventional sensors struggle. Crushing and grinding of ore in the mining sector accounts for roughly 3% of the global total electricity use. Better fragmentation data enables
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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robots and sensor networks increasingly use federated learning (FL) to train shared models across many devices without centralising raw data. In realistic deployments, however, each robot experiences
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/FMV, geospatial and AIS tracks, signals and sensor data, and text-based intelligence reports and develop pipelines, annotation frameworks, and quality assurance processes while gaining deep exposure
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learning algorithms, building thermal image mosaics, collecting and analyzing thermal datasets, and contributing to research on PV health monitoring. Applicants should have a bachelor's degree in Computer