Dr. Johan van Soest
Senior Researcher | Assistant Professor
Johan’s focus is on ELSA aware Data Science, and tools to support this process. He applies these methods and technologies in a various range of projects in the public domain (healthcare and poverty & debt). These methods range from doing data science safely, for example by using privacy-enhancing technologies (PET), to the reporting and ELSA considerations during the data science development process.
Johan holds a MSc in Medical Informatics, and a PhD in Clinical Data Science in Radiotherapy. Due to this background, he is able to switch easily between the practical challenges about using AI (from the non-technical user perspective) and the technical challenges data scientistis/engineers encounter.
Keywords:
- Data Science
- ELSA
- Privacy Enhancing Technologies (PET)
My work at BISS
BETTER: Responsible data analytics in healthcare
In the BETTER project, we are working on the integration of technical (and administrative) aspects with the ethical and societal aspects during AI development.
FAIR4AI: making AI models practically usable
In the suite of FAIR4AI projects, we are improving the practical usability of AI models by implementing the FAIR (Findable, Accessible, Interoperable, Reusable) principles.
Priceless Assets of Subversion: Financial Crime and the Valuation of Unique Goods
In the PRICELESS project, we are improving the detection and prevention of subversive financial crime by examining how high-value unique goods—such as artworks, Non-Fungible Tokens (NFT's) , and luxury watches—are transformed into financialized assets.
Working towards a clear and simple welfare application
We use data and behavioral science to improve the welfare application of a municipality.
AI to prevent poverty and debt
1 in 14 children in the Netherlands grow up in poverty. This is unacceptable, so we are doing something about it!
Inspiration sessions Data science
3 inspiration sessions where participants will get insights and tools to increase the impact of data in their work.
Training Data Interpretation, Ethics & Security
In 2 days, data science will be explained in an interdisciplinary manner using a case from the organization.