I am a postdoctoral researcher in the Machine Learning group at Bielefeld University, where I lead a junior research group on robust life-long machine learning in the research network SAIL: SustAInable Life-cycle of Intelligent Socio-Technical Systems. In order to address important demands for AI systems such as transparency, human agency, safety and resource-efficiency, the interdisciplinary research network SAIL focuses on the full life-cycle of AI systems. Before this, I performed my PhD research in the Intelligent Systems group at the University of Groningen.
Postdoc in Machine Learning
Machine Learning group, Bielefeld University
PhD in Machine Learning
Intelligent Systems group, University of Groningen, PhD thesis
MSc. in Computing Science
University of Groningen
We build a linear dynamical model for complex fluid flows using a Machine Learning architecture based on Koopman theory.
In this work we show theoretically that using GELU activation in neural networks induces continuous phase transitions and we analyse the location of the phase transition. We furthermore introduce and analyse a combination of Erf and GELU activation.
We present a typical Industry 4.0 case study: the real-time quality estimation of steel in a high-throughput production line using Machine Learning methods.
A statistical physics based modelling framework is developed in which we study standard training algorithms (SGD, LVQ1) under concept drift and in addition compare ReLU vs sigmoidal activation.
Our systematic comparison of networks with ReLU and sigmoidal units in model situations reveals surprising differences in their training and generalization behavior.
A multidisciplinary project focusing on transparent AI, human agency, safety and resource-efficiency.
Typical case analysis of machine learning scenarios
Employing AI techniques to model and control dynamical systems.
Using Machine Learning methods to improve health care
Focuses on the development of intelligent, connected and customized production processes
In order to compute weight updates, backpropagation uses complete knowledge of the downstream weights in the network. In [1] it is …