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Artificial Intelligence (AI) models are widely used in decision making procedures in many real-world applications across important areas such as finance, healthcare, education, and safety critical
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at prediction and pattern recognition tasks but still fails at very simple planning and decision-making problems. This project will develop predictive and prescriptive analytics algorithms that combine
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gestural instrument for live electronic music performance, music education and general health and wellbeing in collaboration with our interdisciplinary team at SensiLab. This can be done through new
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-model fusion”. The successful candidate will develop near-real-time integration between emerging environmental and ecological AI-driven data sources (e.g., automated acoustic and machine vision species
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feasibility, and to facilitate the rapid translation of study findings into registry practice and health data environments. Project goals: The aim of the project is to develop cutting-edge AI algorithms