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Field
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of Biomedical Engineering, please visit https://www.bme.ubc.ca/ . HuMBL, a research lab within the SBME, specializes specifically in wearable sensor technologies and algorithm-driven health analytics to enhance
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quality, and real-time AI performance. This research hub, tackles the intricate challenges of cyber-disturbances and data quality in Edge Computing (EC) environments supporting AI algorithms. The role
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/INS systems, RGB-D cameras, LiDAR, radar, IR/hyperspectral cameras, and other sensors. Understanding and experience with development of electrical wiring diagrams, schematics and installation drawings
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languages; writing and testing logic in hardware description languages; developing and testing signal processing algorithms from concept to implementation; and performing systems integration and testing
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and testing software in high level languages; writing and testing logic in hardware description languages; developing and testing signal processing algorithms from concept to implementation; and
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of the fingers, and the positions of tactile sensors), and the control policy for that hand, when given a particular task or set of tasks. Through this, we aim to develop a framework that can automatically
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-driven algorithms which can solve state estimation problems in fluid mechanics, such as inferring the instantaneous state of a fluid’s velocity field from sensors embedded in its boundary. The research
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sustainability. The research will delve into power-aware computing strategies, thermal management, and the development of algorithms that balance performance with energy consumption. Students will aim to create
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set of sensors (LiDAR, RGB, IR, and Spectrometer) that enable advanced plant measurements, that allow us to assess plant’s water budget in response to abiotic stress and nutrients’ application
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complicates both learning and inference processes. Another challenge is that dynamic structured data are generated by a variety of sensors and infrastructures that continuously produce, disseminate, and store