Starting in 2007, I have a research position at Philips Research, originally within the User Experiences Group (former Media Interaction Group) of Reinder Haakma. I was member of the Computational Intelligence (former Interactive Algorithms) cluster headed by Steffen Pauws. In January 2010 groups were reorganized and I worked within the Brain, Body & Behavior Group, headed by Ans Saalberg. In January 2010 groups were reorganized and I worked within the Brain, Body & Behavior Group, headed by Ans Saalberg. In 2011 I moved to the Healthcare Information Management Group of Sybo Dijkstra, later Reinhold Grellmann, which became the Chronic Disease Management Group led by Sybo Dijkstra in 2014, and Aleksandra Tesanovic in 2018. The department was renamed to Department of Collaborative Care Solutions, and later Department of Remote Patient Monitoring and Chronic Care.
Starting December 2010, next to this full-time job, I also performed a Ph.D. at Groningen University, which I successfully defended on 28 November 2014.
In my first 4 years with Philips Research, my work focused on the Lifestyle domain and was around the topic of measuring emotions and stress using physiological measurements (e.g., skin conductance, electrocardiogram, respiration measurements). Key elements in this work are automated feature extraction and interpretation of physiological signals, including classification of interpreted signals, as well as modeling of emotions. Part of this work has been done within the European project named REFLECT, in which I contributed to a demonstrator system, built into a Ferrari sports car.
In 2011 I moved to the Medical domain and started working on the topic of Clinical Decision Support (CDS), focusing at Readmission Management and Discharge Planning in particular for Heart Failure (HF) patients and multi-morbid, chronic patients in general. Later, my clinical domain focus moved to COPD and Parkinson's disease. This work comprises the development of intelligent algorithms and models to quantify and predict patients' risks of various adverse outcomes. My most recent research interest are in explorative data analysis of population health data. This encompasses the application of unsupervised machine learning and natural language processing and natural language generation techniques to obtain actionable insights from patient population data to support clinicians in making better decisions.
My expertise as senior data scientist is in the area of Pattern Recognition/Classification, Machine Learning, Clustering, Data Mining; in particular white-box methods (e.g., prototype based classifying), Signal Processing, Signal Interpretation, Feature Extraction, Mathematical Modeling, Algorithm Development, Clinical Decision Support, Clinical Research, Affective Computing, Physiological Measurements.
On the subpages you can find an overview of my Publications (note that this is my maintained list of publications and that the 'academic profiles', of which you can find icons and links below, might be incomplete and incorrect) and Professional Activities.