Xi Long

Xi Long is an Associate Professor in the Biomedical Diagnostics (BM/d) Lab and Signal Processing Systems (SPS) group at Eindhoven University of Technology (TU/e). He specializes in signal processing, machine learning, and time series analysis applied to healthcare technologies such as unobtrusive vital signs monitoring, sleep studies, neonatal/maternal health, and clinical decision support systems. His work bridges technology and healthcare to create practical solutions for improving patient outcomes.

Education:

• BEng (Hons) in Electronic Information Engineering, Zhejiang University (2002–2006)
• MSc in Electrical Engineering, TU/e (2007–2009)
• PhD in Signal Processing Systems (cum laude), TU/e & Philips Research (2011–2015)

Research Interests:

His research focuses on innovative technologies for health monitoring, including unobtrusive sensing for vital signs, sleep disorder analysis, neonatal care, and AI-driven clinical support. Key areas include:

• Machine learning for healthcare data analysis
• Non-invasive physiological signal processing
• Wearable and remote monitoring systems

Recent Trends in Articles:

Recent work emphasizes multi-modal data fusion for sleep apnea detection, deep learning models for neonatal sleep staging, and AI applications in sepsis prediction. His publications highlight advancements in sensor technology, clinical algorithm validation, and translational healthcare solutions.

Awards and Grants:

• Best Student Paper Award, IEEE BIBE 2012
• First Runner-Up Paper Award, IEEE BHI 2012
• Peer reviewer for grants in multiple European countries

Labs and Collaborations:

He leads projects in the Biomedical Diagnostics Lab and collaborates with Philips Research and industry partners. His work is part of initiatives like the MEDEIA and PISANO projects, focusing on medical engineering innovations and neonatal care technologies.