Naast een wetenschappelijk semesterprogramma organiseert het CWI minisymposia, masterclasses, hackathons en data-challenges. Daarnaast hosten we reguliere wetenschappelijke bijeenkomsten zoals leesgroepen, seminars, samenwerkingssessies en open-probleemsessies. Dit vullen we in op een flexibele manier, waarbij we rekening houden met de voorkeuren van de deelnemers.
Evenementen 2022
Een overzicht van komende CWI evenementen (Nederlands- en Engelstalig)
Inaugural Lecture: Serge Fehr
Everyone is cordially invited to attend the inaugural lecture of Serge Fehr (CWI and University of Leiden), entitled : Quantum information theory - When quantum mechanics and the mathematics of information meet'.
PhD defence Dean De Leo (Database Architectures)
Everyone is invited to attend the public defence of Dean De Leo of his thesis entitled 'Analysing Dynamic Graphs on Sparse Arrays'.
PhD Defence Koen de Boer (CR)
Everyone is welcome to attend the public defense of Koen de Boer (CR) of his thesis 'Random Walks on Arakelov Class Groups'.
PhD Defence Ruben Brokkelkamp (N&O)
Everybody is welcome to attend the public defense of Ruben, of his thesis ' how close does it get? From Near-Optimal Network Algorithms to Suboptimal Equilibrium Outcomes'
QuSoft seminar with Sebastian Zur (QuSoft)
Everyone is welcome to attend the seminar for Sebastian Zur with the title ' Multidimensional Quantum Walks' , at CWI or on-line. For the link please contact Jop Briet.
N&O seminar: Ferenc Bencs (UvA)
Everyone is welcome to attend the next N&O seminar with Ferenc Bencs with the title "A uniqueness result about Gibbs measures"
Dutch Seminar on Optimization (online series) with Ilker Birbil (University of Amsterdam)
The Dutch Seminar on Optimization is an initiative to bring together researchers from the Netherlands and beyond, with topics that are centered around Optimization in a broad sense. We would like to invite all researchers, especially also PhD students, who are working on related topics to join the events.
Multiscale Dynamics Seminar Ajay Tiwari
Machine Learning in Space Weather
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