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Ilenia Salaris

BA, MSc, MBPsS


DPhil Candidate

Neuroscience and Artificial Intelligence

RESEARCH

My research on Spiking Neural Networks (SNNs) builds upon my multidisciplinary background in psychology, neuropsychological rehabilitation, brain-computer interfaces (BCIs), and computational neuroscience. SNNs provide a biologically inspired framework for understanding vision processing, particularly in the area of visual feature binding—the integration of distinct visual elements into a unified and coherent representation. My research focuses on leveraging the temporal dynamics and event-driven nature of SNNs to model how the brain processes visual information efficiently. By studying these mechanisms, I also aim to uncover insights that can enhance current deep learning architectures, improving their efficiency and interpretability while bridging the gap between artificial and biological vision systems. This work also highlights the importance of ethical considerations in the development and deployment of AI technologies.