Wenjin Wang is a guest researcher with the Electronic Systems group and Signal Processing Systems group of the department of Electrical Engineering at Eindhoven University of Technology. His main affiliation is with Philips Research where he works as a scientist. His areas of expertise include biomedical optics, signal/image processing, computer vision, and machine learning. His current research focus is on camera-based vital signs monitoring (e.g. remote photoplethysmography). His earlier PhD work on this topic led to various peer-reviewed journals/conference publications, patent applications, and systems/prototypes that will end in customized applications. Meanwhile, he serves as a reviewer for several well-known journals and conferences. He is also active in academia like organizing workshops/sessions at the top conference.
Wenjin Wang received his BSc in Biomedical Engineering (in the top-class program) from Northeastern University (China) in 2011; his MSc in Artificial Intelligence from University of Amsterdam (The Netherlands) in 2013, with the full scholarship; and his PhD in Electrical Engineering from Eindhoven University of Technology (TU/e, The Netherlands) in 2017, with the PhD thesis "Robust and Automatic Remote Photoplethysmography". His earlier PhD work in camera-based vital signs monitoring led to 11 journal publications (8 times the first author), 4 conference papers (2 times the first author), and 8 patent applications (with Philips Research). After PhD, he joined Philips Research as a scientist, working on contactless monitoring technologies. He is also a guest researcher at TU/e.
Fully-automatic camera-based pulse-oximetry during sleep2018 IEEE conference on computer vision and pattern recognition workshops (CVPR 2018) (2018)
Full video pulse extractionBiomedical Optics Express (2018)
Attacks on heartbeat-based security using remote photoplethysmographyIEEE Journal of Biomedical and Health Informatics (2018)
Robust and automatic remote photoplethysmography(2017)
Camera-based assessment of arterial stiffness and wave reflection parameters from neck micro-motionPhysiological Measurement (2017)
No ancillary activities