Related research
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I am co-director of the 3D Urban Understanding (3DUU) lab, which I started in 2020 with Dr. Liangliang Nan as part of the TU Delft AI Initiative.
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I co-organize the Unsupervised Learning for Automated Driving (ULAD) workshop at the IEEE Intelligent Vehicles Symposium. See links to past editions for ULAD 2019, ULAD 2020.
Past projects and affiliations
Before joining the ME faculty, 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.
Contact address
dr. J. F. P. Kooij
Faculty of Mechanical Engineering
Room 34-E-0-260, Mekelweg 2
2627 CD Delft, The Netherlands