Driven by a deep curiosity about how humans perceive and engage with the world, my research lies at the intersection of cognitive neuroscience and artificial intelligence. With a foundation in the life sciences, I examine human cognition from a neurobiological perspective, focusing on internal representations—how information about the external world is encoded and transformed in the brain. Because humans exist within inherently social and relational environments, I position vision as a central domain of inquiry, given its fundamental role in how we encounter others and the world. I am particularly interested in the representational and computational principles underlying visual cognition. At the same time, I seek to translate insights from human vision into biologically informed AI systems, exploring how principles of visual cognition can be implemented in machines and how machine representations align with human cognition. Ultimately, I aim to clarify the mechanisms of visual representation while developing technologies that extend these capacities, contributing to deeper scientific insight and meaningful human–machine alignment.