Prof. Dr. Martin Butz
Group Leader
My research focus lies in neuro-computational cognitive modeling, machine learning, and cognitive science. I am particularly interested in uncovering and learning conceptual, compositional, causal structures from sensorimotor experiences in humans and with artificial systems. Over the last years, my group also started to model and simulate weather and climate processes and systems.

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Manuela Di Paolo
Administration
I take care of the organization of the Cognitive Modeling Chair. Feel free to contact me with any question regarding this matter!
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Dr. Asya Achimova

Postdoc
I am working on modeling ambiguity resolution as pragmatic inference within the Rational Speech Act framework.
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Dr. Sebastian Otte

Postdoc
My current research focuses on recurrent (spiking) neural networks, adaptive temporal prediction models (in the context of spatiotemporal process modeling), and efficient online learning.
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Christian Gumbsch
PhD
I am interested in the autonomous learning of sensorimotor abstractions for hierarchical prediction, planning, and reinforcement learning.
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Matthias Karlbauer
PhD
I am enthusiastic about applying machine learning techniques, in particular recurrent neural networks, to climate-related topics, such as weather forecasting, which is the core topic of his ongoing PhD research studies.
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Turan Orujlu
I'm interested in intuitive physics for artificial intelligence systems.
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Manuel Traub
I am interested in self-learned and explainable object recognition, object tracking, and object interactions
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Melvin Ciurletti
PhD
I am researching Graph Neural Networks to model complex temporal dynamics like the mechanical responses of meta-materials.
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Fedor Scholz
PhD
I am interested in active inference and how our brain deals with latent object properties such as affordances. Furthermore, I am working on modelling and control of spatio-temporal processes like river discharge with artificial neural networks.
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Johanna Theuer
PhD
My research interests lie in neural networks, Bayesian modeling, Event-Predictive Cognition and Active Inference.
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Max Mittenbühler
PhD
I am investigating how the human cognitive system allocates mental resources to competing information processes (e.g., processing stimulus color and position in a Simon task). To address this question, I aim to develop computational models that can mimic this process and predict empirical data.
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Danil Koryakin
PhD
The area of my research interest is the modular networks on the basis of the recurrent and feed-forward artificial neural networks. The current studies deal with online learning of the compact modular networks and their application for generation and identification of the continuous dynamics as well as for classification of the discontinuous sequence data.
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