Jurgen van den Hoogen

Dr. Jurgen van den Hoogen serves as a Researcher at Tilburg University's Department of Computational Cognitive Science within the Tilburg School of Humanities and Digital Sciences. Having recently completed his doctoral studies with thesis publication in January 2025, he represents an emerging researcher in the field of machine learning applications for time series data.

His research focuses on innovative applications of Convolutional Neural Networks for time series analysis, with particular emphasis on industrial fault detection and seismic activity monitoring. Dr. van den Hoogen's work demonstrates how specialized CNN architectures can effectively process raw sensor data with minimal computational requirements, making them suitable for edge computing applications.

His doctoral research made significant contributions to the field, particularly in developing wide-kernel CNN architectures optimized for time series data processing. The research demonstrated that processing multivariate time series in a univariate manner with separate inputs yields optimal results, and that graph-based architectures significantly improve performance in seismic domains characterized by extensive sensor networks.

Dr. van den Hoogen's methodological expertise includes architectural optimizations through adaptive input layers and residual learning, hyperparameter analysis specifically tailored for time series CNNs, and transfer learning applications for both classification and regression tasks in time series analysis.