Technische Universität Darmstadt
Humanwissenschaften - Computational and Cognitive Neuroscience
I conduct research at the intersection of natural and artificial intelligence. My group uses mathematically rigorous and algorithmically diverse tools to understand the nature of representation and computations that give rise to intelligent behavior, with particular regard to the challenges posed by inferential uncertainty and the opportunities afforded by volitional control. Using diverse machine learning and statistical tools, e.g. Bayesian statistical modeling, control theory, reinforcement learning, and information theory, theoretical frameworks and mathematical models are developed to explain disparate aspects of cognition importation for intelligence: perception, attention, decision-making, learning, cognitive control, active sensing, economic behavior, and social interactions. My lab mainly specializes in theoretical modeling, but also utilizes various experimental methods, e.g. behavior, eye-tracking, fMRI, to help develop and validate the theoretical concepts. In addition, my group collaborates with a number of experimentalists on a range of topics related to human and animal cognition, including neural and psychiatric impairments.
RECOWNs: Probabilistic Circuits for Trustworthy Time Series Forecasting.
Proceedings of the 4th Workshop on Tractable Probabilistic Modeling (TPM 2021).