Katja Seeliger

Dr. Katja Seeliger serves as a Research Fellow at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany, affiliated with the Methods and Development Group for Neural Data Science and Statistical Computing and the Research Group Vision and Computational Cognition.

Her research integrates computational neuroscience, machine learning, and cognitive science to decode neural representations of visual stimuli. She specializes in developing statistical models for fMRI data analysis, with emphasis on object recognition, naturalistic stimulus reconstruction, and high-level visual cortex mapping using deep neural networks. Her methodological innovations bridge neuroimaging with artificial intelligence to model brain information processing.

Analysis of her 2022-2025 publications reveals a cohesive research trajectory centered on large-scale neuroimaging datasets (notably CNeuroMod-THINGS) and attention-based neural decoding architectures. Recurring themes include gaze-informed encoding models, cross-species visual processing comparisons, and interpretable dimensionality reduction for neural representations, demonstrating consistent focus on advancing computational frameworks for visual neuroscience.

Dr. Seeliger actively contributes to the Neural Data Science and Statistical Computing group, where she develops open-source tools for neuroimaging analysis and collaborates on methodological advancements in brain-optimized convolutional neural networks.