I am a PhD candidate in Computational Cognitive Neuroscience in VCCN Lab at Justus Liebig University Giessen.
My research lies at the intersection of visual cognition and computational neuroscience, where I investigate the representational structure of artificial and biological vision systems. During my PhD, I formulate and pursue theory-driven research questions about how internal representations in deep neural networks align with human visual behavior, and under what conditions they diverge.
To address these questions, I develop, train, and systematically probe computational models of vision (e.g., convolutional neural networks), alongside designing and conducting controlled behavioral experiments with human participants. By integrating behavioral data, neuroimaging findings, and computational analyses, I examine how visual biases and perceptual phenomena emerge across different model architectures and training regimes.
My earlier work combines empirical and theoretical approaches to understanding brain function. In my MSc research, I investigated the functional heterogeneity of face-selective regions in the human ventral visual pathway using connectivity fingerprint and representational analyses of fMRI data. In parallel, I explored biologically grounded dynamical systems models of cortical circuits, implementing neural population models to study oscillatory activity and working memory dynamics in the higher-level cortex.
Looking ahead, I am particularly interested in:
- Representational alignment between vision models and human
- Mechanistic interpretability and circuit-level analysis of vision and multimodal models
- Leveraging principles of biological vision to build more robust, fair, and interpretable AI systems