Data Scientist / Researcher at the Innovation Psychiatry department.PsyData: BIG DATA PSYCHIATRIE"In de zorg verzamelen we veel data, zoals tijdens diagnostiek en behandelingen. We kunnen deze informatie nog veel beter gebruiken. Bijvoorbeeld om mentale gezondheid beter te begrijpen en om de dagelijkse zorg te verbeteren. Dit is de essentie van de Big Data Psychiatrie werkwijze: het benutten van de kennis die verborgen zit in data op onze afdeling om de zorg te verbeteren. Hiervoor gebruiken we moderne technieken uit de Data Science en is er nauwe samenwerking tussen zorgprofessionals en data specialisten. Met behulp van Big Data-analyses willen we meer inzicht krijgen in de oorzaak van psychiatrische stoornissen en effectiviteit van behandelingen."https://www.umcutrecht.nl/nl/innovatie-in-de-psychiatrie

Investigating Data Science solutions for different departments throughout the company. I gathered hands-on experience in stakeholder management, big data processing and machine learning.

Develop smart ways of data-driven personalized e-coaching for the behavior change apps Goalie (mental health) and Brightr (employee well-being). My roles and responsibilities:1) AI Expert- Using my expertise in AI to specify approaches for behavior change and coaching.- Working together with domain experts and translating domain knowledge into functionality and modules for the apps.- Specifying implementations to realize now and planning future iterations (PO).2) Researcher- Carrying out research projects (eg. early warning for depression) and writing new proposals (e.g. coaching support dashboard).- Keeping in touch with research groups and facilitating cooperation with PhD students/ interns.- Keeping up to date with research and create a constantly improving model of technology supported behavior change.

How can technology support employees to prevent burn-out? Making use of sensors and smart reasoning. (SWELL project)My research topics:- Machine learning for automatic recognition of mental states (mental effort, emotion, stress) on basis of unobtrusive sensors in the office. Quantified-self and insight into personal data by means of visualization.- Combining possibilities of technology with work stress theory, for behavior change at the workplace. Approaches for e-coaching/ e-health.- User-centered design, taking into account user needs and privacy.Publications: http://cs.ru.nl/~skoldijk/

Research Topic: "Using Sensors to Support Self-management of Well-being"Publications: http://cs.ru.nl/~skoldijk/

During this internship I analysed a multimodal dataset of stress related work behavior by means of visual analytics. The aim was finding personal patterns in sensor data that are indicative of stress.

During this internship I applied different machine learning techniques to infer the current work task from low level computer activity, like applications, clicking and typing behavior.