Apart from a scientific semester programme CWI organizes mini-symposia, masterclasses, lectures with renowned speakers (like the Abel prize winners from 2022), hackathons and data challenges. Additionally, we organize and host other regular scientific meetings like reading groups, seminars, collaboration sessions and open-problem sessions. The format is flexible to meet the preferences of the participants.
Events 2025
Find future and past events.
CHIWORK 2025
The 4th Symposium on Human-Computer Interaction for Work (CHIWORK)
Workshop: Information Disorder Network Netherlands - From hate speech to mis-/disinformation (and beyond)
This workshop is part of the Research Semester Programme Truth is in the Eyes of the Machines.
Workshop on Theory of Control and Reinforcement Learning
As a part of our semester programme, we organise a workshop on “Theory of Control and Reinforcement Learning” on June 19-20, 2025 at CWI, Amsterdam.
SC Seminar Ahmed Elgazzar
Inaugural Lecture and Seminar Jurjen Helmus
On 3 June Jurjen Helmus will deliver his inaugural lecture for the Industrial Digital Twins research group, titled: Future of Industry – Industry of the Future. Prior to the lecture, the research group is organizing an interactive seminar, where you can explore applications of industrial digital twins and related technologies. Additionally, the goal is to collaboratively develop a research agenda with all industrial partners that addresses the current challenges facing the sector.
SC Seminar Jemima Tabeart (TU/e)
Van Dantzig Seminar
Nationwide series of lectures in statistics: speakers Wouter Koolen and Dragi Anevski
Workshop: Information Disorder Network Netherlands - From mis-/disinformation to hate speech (and beyond)
This Research Semester Programme is part of Truth Is in the Eyes of the Machines. How do misinformation and hate speech fuel and influence each other? How can sustainable and FAIR data (Findable, Accessible, Interoperable and Reusable) be developed to independently investigate misinformation and hate speech? How robust are generative AI models at detecting and actively countering information disorders?
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