I am an Assistant Professor at the Intelligent Vehicles group, performing research and education on autonomous driving and vehicle perception. The group is part of the Cognitive Robotics department of the 3ME faculty, TU Delft, The Netherlands. You can find my staff page on the TU Delft website.
My research interests include statistical machine learning and probabilistic inference for sensor processing (computer vision), environment understanding, and predictive models of Vulnerable Road User (VRU) behavior. Good predictive models of VRU behavior are essential for automated vehicles to guide their decision making and trajectory planning. This is especially true for the challenging urban environment, where interactions with VRUs are frequent.
Before joining 3ME, I was a PostDoc at the computer vision lab of the EWI Faculty of TU Delft. In this period, I worked on setting up the new Technology In Motion (TIM) lab at LUMC hospital in Leiden, and developed new signal processing techniques to detect subtle tremors in patients. My PhD at the University of Amsterdam addressed automated analysis of pedestrian tracks, using probabilistic graphical models for unsupervised learning and online predictive Bayesian inference. For the NWO Cassandra and EU-FP7 ADABTS projects, I developed graphical models for the integration of audio-visual cues, and for anomaly detection, in surveillance applications.
In 2013 I interned at the Environment Perception group of Daimler AG in Ulm, Germany. There, I worked on improved pedestrian path prediction for intelligent vehicles, exploiting various contextual cues such as pedestrian head orientation and location relative to the road.
dr. J. F. P. Kooij Faculty of Mechanical, Maritime and Materials Engineering Room 34-E-0-260, Mekelweg 2 2627 CD Delft, The Netherlands