Bio

I am an Assistant Professor in the Department of Cognitive Sciences and Artificial Intelligence. My research focuses on artificial intelligence for image and video analysis.  In particular, I am interested in segmentation of biomedical images and tracking of multiple agents to automatically extract insightful information and to create computational models.

Prior to joining Tilburg University, I was a Research Scientist at the Singapore-MIT Alliance for Research and Technology (SMART) Centre in the BioSystems and Micromechanics (BioSyM) interdisciplinary research group. I received my PhD degree in Field Robotics from the University of Sydney, Australia in 2008. I received a Bachelor of Engineering (Mechatronics) from the University of Sydney in 2003. 

Expertise

Image Analysis, Object Tracking, Information Fusion, Machine Learning, Stochastic Filtering, Bayesian Estimation

Courses

Recent publications

  1. Predicting Vasovagal Reactions to Needles from Facial Action Units

    Rudokaite, J., Ertugrul, I. O., Ong, S., Janssen, M. P., & Veld, E. H. I. . (2023). Predicting Vasovagal Reactions to Needles from Facial Action Units. Journal of Clinical Medicine, 12(4), 1-14. [1644].
  2. Predicting vasovagal reactions to a virtual blood donation using faci…

    Rudokaite, J., Ong, LL. S., Janssen, M. P., Postma, E., & Veld, E. H. I. . (2022). Predicting vasovagal reactions to a virtual blood donation using facial image analysis. Transfusion, 62(4), 838-847.
  3. Superpixel-based Context Restoration for Self-supervised Pancreas Seg…

    van Donkelaar, S., Daamen, L., Andel, P., Zoetekouw, R., & Ong, S. (2022). Superpixel-based Context Restoration for Self-supervised Pancreas Segmentation from CT scans. Paper presented at 34rd Benelux Conference on Artificial Intelligence and the 31th Belgian Dutch Conference on Machine Learning , Mechelen, Belgium.
  4. Producing "Open-Style" Choreography for K-Pop Music with Deep Learning

    Ban, S., & Ong, S. (2021). Producing "Open-Style" Choreography for K-Pop Music with Deep Learning. Abstract from 33rd Benelux Conference on Artificial Intelligence and the 30th Belgian Dutch Conference on Machine Learning , Luxembourg, Luxembourg.
  5. Development and Validation of a Convolutional Neural Network for Auto…

    Hendrix, N., Scholten, E., Vernhout, B., Bruijnen, S., Maresch, B., de Jong, M., Diepstraten, S., Bollen, S., Schalekamp, S., de Rooij, M., Scholtens, A., Hendrix, W., Samson, T., Ong, S., Postma, E., van Ginneken, B., & Rutten, M. (2021). Development and Validation of a Convolutional Neural Network for Automated Detection of Scaphoid Fractures on Conventional Radiographs. Radiology: Artificial Intelligence, 3(4), e200260. [e200260].

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