Rate My Professor Maarten De Vos

De Vos's research centers on biomedical data processing, artificial intelligence in healthcare, innovative health technologies, biomedical signal processing, and medical technology design. He pioneered mobile brain imaging technology, enabling reliable physiological measurements of brain and body functions in unconstrained, out-of-lab environments, and develops AI solutions for deriving personalized biosignatures of patient health within unobtrusive systems. Prominent publications encompass "Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal" (BMJ, 2020), "SeqSleepNet: end-to-end hierarchical recurrent neural network for sequence-to-sequence automatic sleep staging" (IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2019), "Joint classification and prediction CNN framework for automatic sleep stage classification" (IEEE Transactions on Biomedical Engineering, 2018), "How about taking a low-cost, small, and wireless EEG for a walk?" (Psychophysiology, 2012), and "Source separation from single-channel recordings by combining empirical-mode decomposition and independent component analysis" (IEEE Transactions on Biomedical Engineering, 2010). His achievements include awards such as the Mobile Brain Body Imaging prize (2017), Martin Black prize (2019), IEEE EMBS best paper award (2021), and the George B. Moody PhysioNet Challenge win. De Vos holds positions as Associate Editor for IEEE Journal of Biomedical and Health Informatics and editorial board member for Journal of Neural Engineering and Nature Digital Medicine.