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longer sustainable. This project pioneers a new paradigm: we design smart, low-power digital AI co-processors that learn and correct the imperfections of their analog counterparts in real-time. As a PhD
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society. We are a major part in implementing the 2030 vision of the Faculty of Medicine, i.e. to become leading within digital health and well-known for doctors and engineers finding solutions together. Our
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research group in computer vision and machine learning, with seminal results in 3D reconstruction from images, scene understanding, deep learning, optimization, sparsity, etc. IMAGINE is part of
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
developed a dataset by conducting high-velocity impact experiments on CFRP specimens using controlled testing setups. The multimodal dataset is to be processed using X-ray CT scans, SEM imaging, and
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imaging systems capable of penetrating fog, dust, and even certain solid materials. These systems will deliver detailed, high-resolution imaging in challenging conditions where conventional optical sensors
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AI design of ultrathin lenses for compact imaging devices The Faculty of Engineering at the University of Nottingham is seeking an enthusiastic, self-motivated student who enjoys working as part of
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AI design of ultrathin lenses for compact imaging devices The Faculty of Engineering at the University of Nottingham is seeking an enthusiastic, self-motivated student who enjoys working as part of
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, various digital tools have emerged to address these needs: mobile apps, training software, and communication aids (Oussama et al., 2021; Phosanarack et al., 2025). Although promising, these technologies
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human robot interaction (e.g., sensory adaptive, child-led, reciprocal AI) Develop LLM-driven dialogue systems integrated into robotic and/or digital platforms Prototype and evaluate multimodal interfaces
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, Diffusion Tensor Imaging (DTI), Ultrasound, muscle stimulation, electromyography (EMG), and motion capture. Conducting human anatomical specimen dissection studies to obtain in-vitro data for model