teaching

MInformation on guest lectures I have given

Guest Lectures

Currently I am only giving guest lectures for some courses at the HAN. In addition I am involved in developing educational material for the Master Applied Data Science (see MADS)

HAN

  • 2023-now: several classes in Master Applied Data Science
  • 2022-2023: Machine Learning (linear regression) in ‘Minor Data Science’ - HAN University of Applied Sciences
  • 2020-2022: Text Mining in ‘Minor Data Science’ - HAN University of Applied Sciences
  • 2019-2022: Artificial Intelligence & Deep Learning in ‘Smart Vehicles’ - HAN University of Applied Sciences
  • 2020-now: “van BI naar AI” in ‘BIM Jaar 3’ - HAN University of Applied Sciences

Radboud University

PhD projects

I am co-promotor of 2 PhD students within the HAN:

  • 2024 Swarupa Hardikar on Concept Mining
  • 2022 Inge van Schie on Deep Learning for blood flow analysis

Graduation projects

I have also been a supervisor / second reader on several graduation projects:

  • 2023 Jaimy Göertz (Radboud University) Using concept mining for business-oriented data management: an explorative study
  • 2023 Noud Wijngaards (Fontys): Text Mining voor onderzoek
  • 2022 Akhil Gopinath (HAN) Investigation on Quantifying Driving Proficiency of Novice Drivers by Fusing Modern Data Sources
  • 2021 Fleur Bosman & Diede Otten (HAN) “Denk je ook aan mij?” Een onderzoek naar hoe jongeren met een lage sociaaleconomische status beter kunnen worden betrokken bij onderzoek
  • 2021 Virginia Meijer (Radboud University) Automatically summarizing Dutch human-machine dialogues using transfer learning approaches
  • 2019 Klaus Lux (Radboud University / FD Mediagroup) On the factual correctness and robustness of deep abstractive text summarization
  • 2017 Marjolein de Vries (Utrecht University / TNO) Machine Learning for Sentiment Analysis of Children’s Diaries
  • 2016 Paul Verhaar (Utrecht University / TNO) Radical Reddits: into the Minds of Online Radicalised Communities
  • 2014 Thymen Wabeke (Radboud University / TNO) Recommending tips that support well- being at work to knowledge workers