Ashley de Bie

Ashley de Bie serves as a University Researcher at Eindhoven University of Technology within the Department of Electrical Engineering's Signal Processing Systems group. She is deeply embedded in the Eindhoven MedTech Innovation Center, a strategic partnership between TU/e and Catharina Hospital that drives medical technology translation into clinical practice. Her work directly addresses UN Sustainable Development Goals for health and well-being through engineering-clinical collaborations.

Her research centers on machine learning applications for critical care, with three core thrusts: (1) developing and validating early warning systems like the Advanced Alert Monitor for patient deterioration detection; (2) creating computational tools for mechanical ventilation optimization, particularly in identifying patient-ventilator asynchrony; and (3) designing clinical decision support systems such as the TraceBook tool for individualized patient management. This work consistently bridges algorithm development with real-world hospital implementation.

Analysis of her 2022-2025 publications reveals a strong trend toward context-specific validation of medical algorithms in Dutch healthcare settings. Key patterns include local optimization of international models, integration of clinician feedback in design cycles, and rigorous multicenter trials like the PRECISe study on critical care nutrition. Her publications demonstrate exceptional translational impact, with several tools already deployed in hospital workflows.

With 349 Scopus citations and significant media attention (8 press mentions, 121 X posts, 101 Mendeley readers), her work resonates across academic and clinical communities. The PlumX metrics show particularly strong clinical uptake, with news coverage and social media engagement indicating real-world relevance.

Dr. de Bie has supervised 5 students and maintains a robust collaborative network spanning TU/e's engineering departments and Catharina Hospital's clinical units. Her projects consistently involve multidisciplinary teams of data scientists, biomedical engineers, intensivists, and nurses, reflecting the complex nature of healthcare innovation.

As a core contributor to the Signal Processing Systems group and Eindhoven MedTech Innovation Center, she operates within a dynamic ecosystem focused on rapid prototyping and clinical validation of medical technologies. Her current work with the Advanced Alert Monitor team exemplifies this environment, where algorithms move from simulation to hospital wards within months.