Xi Long
Department / Institute
RESEARCH PROFILE
Xi Long is an Associate Professor in the Biomedical Diagnostics (BM/d) lab, Signal Processing Systems (SPS) group, where he advises, coordinates and participates in many collaborative projects (with, for example, Philips, Máxima Medical Center, Kempenhaeghe, UMC Utrecht, KU Leuven and Fudan University) combining technology and healthcare.
Long’s expertise is in signal processing, time series analysis, machine learning, deep learning and mathematical modeling. His research interests include engineering for biomedical applications such as unobtrusive sensing, vital signs monitoring, sleep, neonatology & pregnancy, epilepsy & brain activity, and clinical decision support.
I always believe opening my eyes to see different worlds will encourage me to think about things that better our life.”
ACADEMIC BACKGROUND
Xi Long holds a BEng with honor in electronic information engineering from Zhejiang University in China and obtained his MSc in electrical engineering from the Eindhoven University of Technology (TU/e) in 2009. He worked at Tencent China as a project manager and UX researcher from 2009 to 2011. He went on to do his PhD at TU/e and Philips Research, on signal processing and machine learning in unobtrusive sleep monitoring, which he completed cum laude in 2015. He then joined Philips Research in 2016 and worked as a senior scientist and AI/Data lead, where he has been also a part-time assistant professor at the TU/e.
Long is an senior member of IEEE, an associate editor of Frontiers in Digital Health, and an editorial board member Health Informatics Journal. He has published over 120 scientific articles and reports, generated more than 15 patents and supervised more than 40 PhD/MSc students. He is a peer reviewer for many leading international journals and conferences in his research areas.
Key Publications
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A review on atrial fibrillation detection from ambulatory ECG
IEEE Transactions on Biomedical Engineering (2024) -
Epileptic seizure detection by cascading isolation forest-based anomaly screening and EasyEnsemble
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2022) -
A deep transfer learning approach for wearable sleep stage classification with photoplethysmography
NPJ Digital Medicine (2021) -
Wearable sensing and telehealth technology with potential applications in the coronavirus pandemic
IEEE Reviews in Biomedical Engineering (2021) -
Audio-based snore detection using deep neural networks
Computer Methods and Programs in Biomedicine (2021)
Current Educational Activities
Ancillary Activities
No ancillary activities