Teaching
Information on guest lectures I have given
Guest Lectures
Currently I am only giving guest lectures for some courses at the HAN and the Radboud University. In addition I am involved in developing educational material for the Master Applied Data Science (see MADS)
HAN
- 2023: several classes in Master Applied Data Science
- 2022: Machine Learning (linear regression) in âMinor Data Scienceâ - HAN University of Applied Sciences
- 2020-2022: Text Mining in âMinor Data Scienceâ - HAN University of Applied Sciences
- 2019-2022: Artificial Intelligence & Deep Learning in âSmart Vehiclesâ - HAN University of Applied Sciences
- 2020-now: âvan BI naar AIâ in âBIM Jaar 3â - HAN University of Applied Sciences
Radboud University
- 2018-2022: Summarization in âText Miningâ - Radboud University
- 2017-2019: Authorship Attribution in âText Miningâ - Radboud University
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) âDenk je ook aan mij?â 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 Childrenâs 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