I am a PhD researcher in deep learning and computational neuroscience at Aalto University, Finland. My research explores how biological systems, especially the human brain, process visual information. I focus on developing deep learning paradigms that more accurately capture the mechanisms of human visual perception and spatial reasoning.
This pursuit is driven by the impetus to gain valuable insights into brain function, particularly through the lens of visual cognitive tasks such as mental rotation and the pop-out effect—whereby an outlier directly attracts attention.
Moreover, I aim to address the limitations of current deep learning models in terms of robustness and efficiency in comparison to human visual systems, while tackling the contemporary challenge of excessive data requirements for model training.
To this end, I am investigating how concepts like symmetry (pose transformations) can enhance machine learning models and lead to more structured representations that generalize to new vision and spatial reasoning tasks.
My hypothesis is that humans can factorize and compose, enabling compact representations by identifying structural patterns through latent symmetries.