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. The project focuses on developing an integrated approach that combines machine learning techniques with physics-based models to estimate the health of various system components. The aim is that fault diagnosis
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to control the electronic properties of organic semiconductors through chemical doping. The work will combine molecular and materials design with advanced structural, spectroscopic, electrical, and
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communication limitations, adversarial conditions, continual and adaptive learning in dynamic environments. The research will combine tools from distributed optimization, stochastic approximation, information
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project developing advanced SERS-based diagnostic technologies for rapid detection and characterization of wound infections. The work combines materials development, spectroscopy, and biomedical validation