Current courses

Open projects

Please contact me for open Research Internships, BSc thesis and MSc thesis projects.

  • Federated Search (Data Science):
    Research approaches that combine the results from multiple, independent and non-cooperative (in the sense that they do not share their index) search engines
  • Federated Learning (Data Science):
    Research approaches that divides machine learning over multiple independent and private data sources
  • Conversational Search (Data Science):
    Can we use techniques from information retrieval or machine learning to improve open source virtual assistants like Stanford’s Almond?
  • COVID-19 search:
    Design a search engine for researches that work on cures and vaccins of COVID-19
  • Ephemeral Social networking (Software Science):
    Based on the W3C standard ActivityPub, design an ephemeral social network (in which most posts are removed after some time) and compare its network/storage/memory/cpu load compared to durable solutions like Mastodon.
  • Secure federated communication (Digital Security):
    Design/adapt an end-to-end encrypted solution for ActivityPub-based social networking: How to handle multiple devices and heterogeneous networks?
  • Transitioning the RU to self-hosted, federated, solutions (Information Sciences):
    For, for instance, self-hosted web analytics, social networking, or video streaming: What are the user requirements? What solutions meet these requirements? What are additional benefits (for instance more autonomy for employees and students)? How to show this with a proof-of-concept.
  • With Nedap Healthcare, Groenlo Machine Learning and Natural Language Processing:
    Clinical Natural Language Processing / De-identification of medical records.
  • Ranking for Clarin (European Research Infrastructure for Language Resources and Technology) federated content search:
    How to model ranking, and how does it improve the quality (and efficiency) of Clarin’s content search engine?

Past courses

Teaching information