Prof. Dr. Martin Butz
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.
Manuela Di Paolo
I take care of the organization of the Cognitive Modeling Chair. Feel free to contact me with any question regarding this matter!
Dr. Asya Achimova
I am working on modeling ambiguity resolution as pragmatic inference within the Rational Speech Act framework.
Dr. Sebastian Otte
My current research focuses on recurrent (spiking) neural networks, adaptive temporal prediction models (in the context of spatiotemporal process modeling), and efficient online learning.
I am interested in the autonomous learning of sensorimotor abstractions for hierarchical prediction, planning, and reinforcement learning.
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.
I'm interested in intuitive physics for artificial intelligence systems.
I am interested in self-learned and explainable object recognition, object tracking, and object interactions
I am researching Graph Neural Networks to model complex temporal dynamics like the mechanical responses of meta-materials.
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.
My research interests lie in neural networks, Bayesian modeling, Event-Predictive Cognition and Active Inference.
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.
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.
... thank you for all the efforts you have put into COBOSLAB / the Cognitive Modeling Team - and all the best for your future!
Dr. Johannes Lohmann
Dr. Fabian Schrodt
PD Dr. Anna Belardinelli
Dr. Andreas Alin
PD Dr. Oliver Herbort
Dr. Jan Kneissler
Dr. Gerulf Pedersen
Dr. Patrick Stalph
Dr. Yuuya Sugita