Daniela is a PhD student in the EDA group and affiliated with the Data Science Research Program. Her PhD project focuses on pattern mining in complex data from observations, medical records and sensors. The data is collected to accompany a change in care management at a nursing home in the Netherlands.
The project is part of a collaboration between Nivel (Dutch Research Organization for Health Sciences) and Stichting Maasduinen, a provider for elderly home and residential care in the South of the Netherlands. Other partners are Actiz and Alzheimer Nederland, the project is funded by ZonMW.
Daniela's current research combines two fields: Computer Science and Health Sciences. The aim is to develop methods to extract patterns from complex data, such as observations, sensor data and medical records. Patterns are extracted to help researchers with exploratory work and ultimately to generate new research hypotheses.
Daniela holds both, a Master's degree in Statistics and in Clinical Neuropsychology from Leiden University.
For her Master in Psychology, she wrote a thesis on the cognitive phenotypes of children with Neurofibromatosis type I at the Erasmus Medical Center in Rotterdam. She did her clinical internship at a neuropediatric clinic in Germany (Schönklinik Vogtareuth).
For her Master in Statistics, she wrote her thesis with her current PhD supervisor Matthijs van Leeuwen, suggesting a way to extract subgroups from dynamic networks by leveraging information theoretic data mining. She did her research internship at Fraunhofer Institute in St. Augustin, Germany, where she focused on non-linear independent component analysis.
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