Kamila Jozwik

Kamila Jozwik

Associated Research Module: 

Associated Research Thrust: 

I am a Sir Henry Wellcome fellow currently working with Jim DiCarlo and Nancy Kanwisher at MIT and the University of Cambridge. I am interested in modelling the visual object representations in the brain and behaviour, for human and monkey, using deep neural networks and conceptual models. 

Research interests

Broadly I'm interested in the following questions:

  • How does the primate brain process visual information? 
  • More specifically - how does the primate brain recognise objects? 
  • What are the underlying computations of visual processing? 

I use fMRI, EEG, MEG, behavioural measures and single-cell recording data, together with computational modelling to understand these processes better. 


After the completion of a BSc in Biotechnology at the University of Warsaw, I did an MPhil and a PhD in Biological Sciences at the University of Cambridge. My PhD was in the field of breast cancer genomics where I worked with Jason Carroll. I collaborated with Simon Baron-Cohen using genomics techniques in autism research. During the PhD, in parallel to the genomics research, I started working with Marieke Mur and Niko Kriegeskorte to gain experience in cognitive computational neuroscience, investigating feature-based and categorical representations in object recognition. Subsequently, I was a Humboldt fellow working with Radek Cichy at the Free University Berlin, studying animacy dimensions in object recognition and comparing words and images object representations.




Jozwik, K.M., Kietzmann, T.C., Cichy, RM., Kriegeskorte, N., Mur, M. (2023)

"Deep neural networks and semantic models explain complementary components of human ventral-stream representational dynamics” Journal of Neuroscience, corresponding author

Jozwik*, K.M., O'Keeffe*, J., Storrs*, K.R., Guo, W., Golan, T., Kriegeskorte, N. (2022)

"Face dissimilarity judgements are predicted by representational distance in morphable and image-computable models" Proceedings of the National Academy of Sciences (*contributed equally), corresponding author


Jozwik, K.M., Najarro, E., van den Bosch, JJF., Charest, I., Cichy*, RM. and Kriegeskorte*, N. (2022)

"Disentangling five dimensions of animacy in human brain and behaviour" Communications Biology, corresponding author


Jozwik, K.M. (2021)

"What AI can learn from the biological brain" Science (book review)


• Adhya, D., Swarup, V., Nagy, R., Dutan, L., Shum, C., Valencia-Alarcón, E.P., Jozwik, K.M., Mendez, M.A., Horder, J., Loth, E., Nowosiad, P., Lee, I., Skuse, D., Flinter, F.A., Murphy, D., McAlonan, G., Geschwind, D.H., Price, J., Carroll, J., Srivastava, D.P., Baron-Cohen, S. (2021)

"Atypical neurogenesis in induced pluripotent stem cell (iPSC) from autistic individuals" Biological Psychiatry (designed initial genomics analyses and processed samples, collaboration initiator)


• Cichy, R.M., Kriegeskorte, N., Jozwik, K.M., van den Bosch, J.J.F., Charest, I. (2019)

"The spatiotemporal neural dynamics underlying perceived similarity for real-world objects" Neuroimage (collected and analysed part of the behavioural data)


Jozwik, K.M., Kriegeskorte, N., Storrs, K.R., Mur, M. (2017)

"Deep convolutional neural networks outperform feature-based but not categorical models in explaining object similarity judgments" Frontiers in Psychology, corresponding author


Jozwik, K.M., Kriegeskorte, N., Mur, M. (2016)

"Visual features as stepping stones toward semantics: Explaining object similarity in IT and perception with non-negative least squares" Neuropsychologia


Jozwik, K.M., Chernukhin, I., Serandour, A.A., Nagarajan, S., Carroll, J.S. (2016)

"FOXA1 directs H3K4 monomethylation at enhancers via recruitment of the methyltransferase MLL3" Cell Reports


Jozwik, K.M., Carroll, J.S. (2012)

"Pioneer factors in hormone dependent cancers" Nature Reviews Cancer




Jozwik, K.M., Lee, H., Kanwisher, N. and DiCarlo, J.J. (2019)

”Are topographic deep convolutional neural networks better models of the ventral visual stream?” Conference on Cognitive Computational Neuroscience


Jozwik, K.M., Kriegeskorte, N., Cichy, R.M., Mur, M. (2018)

”Deep convolutional neural networks, features, and categories perform similarly at explaining primate high-level visual representations” Conference on Cognitive Computational Neuroscience


Jozwik, K.M., Charest, I., Kriegeskorte, N. and Cichy, R.M. (2017)

”Animacy dimensions ratings and approach for decorrelating stimuli dimensions” Conference on Cognitive Computational Neuroscience




• Lee, H., Margalit, E., Jozwik, K.M., Cohen, M.A., Kanwisher, N., Yamins, D.L.K, DiCarlo, J.J. (2020).

”Topographic deep artificial neural networks reproduce the hallmarks of the primate inferior temporal cortex face processing network” (performed analyses on wiring cost calculations and neural fits). bioRxiv


Jozwik, K.M., Schrimpf, M., Kanwisher, N. and DiCarlo, J.J. (2019)

"To find better neural network models of human vision, find better neural network models of primate vision"} bioRxiv


Jozwik, K.M., Lee, M., Marques, T., Schrimpf, M., Bashivan, P. (2019)

"Large-scale hyperparameter search for predicting human brain responses in the

Algonauts challenge"} bioRxiv


Email:  kmjozwik@mit.edu
Room:  46 - 6157

CBMM Publications