Rate My Professor Kamila Jozwik

Her research investigates visuo-semantic cognition in healthy individuals and those with mental health disorders, utilizing cognitive computational neuroscience, NeuroAI, and neurotechnology approaches. She examines visual dimensions in faces, animacy, and objects through behavioural experiments, fMRI, M/EEG, collaborative macaque electrophysiology, machine learning analyses, and biologically inspired deep neural networks. Jóźwik has received the Alexander von Humboldt Postdoctoral Fellowship at Freie Universität Berlin with Radek Cichy, the Sir Henry Wellcome Postdoctoral Fellowship at MIT with Jim DiCarlo and Nancy Kanwisher, and the Royal Society University Research Fellowship. Notable publications include 'Deep Neural Networks and Visuo-Semantic Models Explain Complementary Components of Human Ventral-Stream Representational Dynamics' (Journal of Neuroscience, 2023), 'Disentangling five dimensions of animacy in human brain and behaviour' (Communications Biology, 2022), 'Face dissimilarity judgments are predicted by representational distance in morphable and image-computable models' (PNAS, 2022), and 'Deep Convolutional Neural Networks Outperform Feature-Based But Not Categorical Models in Explaining Object Similarity Judgments' (Frontiers in Psychology, 2017). She contributes to Cambridge NeuroWorks, advancing neurotechnology and mental health applications with non-invasive focused ultrasound and generative AI.