Hey there! I’m Daan.

I am a freelance data scientist and privacy engineer working on projects that make a positive impact on society.

In the past I have worked on systems based on machine learning to detect the risk of cancer development. In addition, I develop technologies that allow for safer data access and sharing, without having to compromise on privacy.

Finally, I also co-founded the collective Dev For Good, a group of developers that aim to use their complementary technical backgrounds to work on projects that drive positive change.

Based in Maastricht but enjoy traveling and working from different places. In my spare time I play bass and guitar.

Resume

Experience

  • 2024-present: Dev for Good, remote

  • 2023-present: Cancer Registry of Norway, Oslo

  • 2021-present: Knoors Data Science, Maastricht

  • 2019-2023: Netherlands Comprehensive Cancer Organisation (IKNL), Eindhoven

  • 2018-2019: Conclusion, Heerlen

  • 2018: Privitar, London

  • 2017: Bridge for Billions, Madrid

  • 2017: Synergic Partners (Telefónica), Madrid

Education

  • 2017-2018: KTH Royal Institute of Technology, Stockholm, Master in Data Science (Double Degree)

  • 2016-2017: Universidad Politécnica de Madrid, Master in Data Science (Double Degree)

  • 2013-2016: University of Technology Eindhoven, Bachelor in Industrial Engineering

Publications

  • Severin Elvatun, Daan Knoors, Mari Nygård, Anneli Uusküla, Andres Võrk, Jan F. Nygård (2024). “Cross-population evaluation of cervical cancer risk prediction algorithms”, International Journal of Medical Informatics.

  • Siri Larønningen, Anna Skog, Gerda Engholm, Jacques Ferlay, Tom Børge Johannesen, Marnar Fríðheim Kristiansen, Daan Knoors, et al (2023). “Nordcan.R: A New Tool for Federated Analysis and Quality Assurance of Cancer Registry Data.”, Frontiers in Oncology.

  • Linda de Munck, Daan Knoors, Harm Buisman, Koen Scholman, Janneke Verloop, Sabine Siesling, (2022). M1 registration: Signaling patients who develop metachronous metastases after primary breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium.

  • Marten Dooper (2022). “LANCELOT analyseert patiëntendata met optimale bescherming privacy”, Interview Ton Peters, Daan Knoors, Thomas Rooijakkers, Oncologie.nu.

  • Bart Kamphorst, Thomas Rooijakkers, Thijs Veugen, Matteo Cellamare & Daan Knoors (2022). “Accurate training of the Cox proportional hazards model on vertically-partitioned data while preserving privacy”, BMC Medical Informatics and Decision Making.

  • Kamphorst, Bart, Daan Knoors, and Thomas Rooijakkers (2021). “Oncological Research on Distributed Patient Data: Privacy Can Be Preserved!”, ERCIM News 126.

  • Daan Knoors (2018). “Utility of Differentially Private Synthetic Data Generation for High-Dimensional Databases”, KTH Royal Institute of Technology, School of Electrical Engineering and Computer Science (EECS).