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of crime death from drowning. Most of the current forensic investigation for non-human biological evidence is primarily linked with the analyses of terrestrial environment, however, there is a demand for a
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to develop specialized deep learning architectures for analyzing drawing tests and human finger motions, with applications in diagnostics, cognitive assessment, and fatigue detection. The Ph.D. candidate will
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solutions with considerable potential impact on essential areas of human life such as environmental protection and medical diagnostics. Employing the molecular imprinting technology, the group designs and
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, maritime transport heavily depended on human capabilities in decision making with the help of marine sensors readouts, charts, etc. With the recent developments in deep learning, sophisticated intelligent
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and cognitive function, with applications in medical fields. The project aims to develop AI-powered digital twins capable of generating synthetic data mimicking human drawing behavior under varying
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its effectiveness, and assessing its economic implications. Ultimately, this research contributes to better grid management and resource allocation in the face of evolving energy demands and generation
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of green energy sources and the reliable operation of the grid in the face of increasing renewable energy penetration and EVs adoption. Responsibilities and (foreseen) tasks Conducting a comprehensive