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-Machine Interfacing for Semi-Autonomous Robotic Prostheses This project will develop novel AI algorithms to decode human intention from electrophysiological signals (e.g., EMG) for intuitive control
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for behavioural and security properties; efficient algorithms for model checking, learning and synthesis; improved explainability and safety of machine learning models, e.g. by integrating neural and symbolic
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, generative design, building performance optimization, digital design methods (e.g., predictive modeling, multi-agent systems and algorithmic techniques for architectural design), digital design epistemologies
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