Erik Korsten

Erik Korsten is a Part-time Professor at Eindhoven University of Technology (TU/e) in the Department of Electrical Engineering's Signal Processing Systems group, while concurrently serving as an anesthesiologist-intensivist at Eindhoven's Catharina Hospital and holding a part-time professorship at Zhejiang University, China. His dual expertise bridges clinical medicine and engineering, focusing on translating signal processing innovations into healthcare solutions through affiliations with the Eindhoven MedTech Innovation Center (e/MTIC) and EAISI Health.

His academic foundation includes a Medical degree from Groningen University (1979), anesthesiology specialization from St. Antonius Hospital Utrecht (1982), and a PhD from Leiden University (1984).

• Groningen University: MD (1979)
• St. Antonius Hospital Utrecht: Anesthesiology Specialization (1982)
• Leiden University: PhD (1984)

Korsten's research centers on clinical decision support systems and medical signal processing, with emphasis on reducing medication errors through tools like the Gaston software for Dutch Electronic Patient Files. His fingerprint reveals deep engagement in hemodynamic monitoring, ultrasound data analysis, and Business Process Model and Notation applications in intensive care. Recent work demonstrates a pivot toward causal inference in observational studies and AI-driven sensor systems for perioperative care, reflecting growing integration of machine learning in critical care analytics.

With 190 publications and 28 supervised works, his output shows sustained productivity through 2024. Current projects focus on therapeutic recirculation measurement via photonic sensors, radial artery catheterization techniques, and adverse drug reaction detection algorithms—highlighting consistent translation of engineering solutions to anesthesiology and critical care challenges.

Korsten actively contributes to UN Sustainable Development Goal 3 (Good Health and Well-being) through hospital protocol optimization and error reduction systems. His supervised works and datasets (including Zenodo repositories for causal inference and early warning scoring systems) indicate strong mentorship in health data science, though specific grant details remain unreported in the source material.

He operates at the TU/e-Catharina Hospital interface within the Eindhoven MedTech Innovation Center, collaborating internationally (notably with China's Zhejiang University) on ultrasound-guided procedures and hemodynamic parameter validation. Current efforts target real-time clinical decision support using integrated sensor networks and deconfounded observational study methodologies.