CLIC-IT: Learning communities as innovation acceleratorIn the past decades, we have faced an increase in the digitization, digitalization, and digital transformation of our work and daily life. Breakthroughs of digital technologies in fields such as artificial intelligence, telecommunications, and data science bring solutions for large societal questions but also pose a new challenge: how to equip our (future) workforce with the necessary digital skills, knowledge, and mindset to respond to and drive digital transformation? Developing and supporting our human capital is paramount and failure to do so may leave us behind on individual (digital divide), organizational (economic disadvantages), and societal level (failure in addressing grand societal challenges). Digital transformation necessitates continuous learning approaches and scaffolding of interdisciplinary collaboration and innovation practices that match complex real-world problems. Research and industry have advocated for setting up learning communities as a space in which (future) professionals of different backgrounds can work, learn, and innovate together. However, insights into how and under which circumstances learning communities contribute to accelerated learning and innovation for digital transformation are lacking. In this project, we will study 13 existing and developing learning communities that work on challenges related to digital transformation to understand their working mechanisms. We will develop a wide variety of methods and tools to support learning communities and integrate these in a Learning Communities Incubator. These insights, methods and tools will result in more effective learning communities that will eventually (a) increase the potential of human capital to innovate and (b) accelerate the innovation for digital transformation.Read more
Training: Introduction to Geospatial Raster and Vector with RIn this training workshop, organized by the Center of Expertise in Big Geodata Science (CRIB), participants will embark on a journey through the fundamentals of geospatial data analysis using R. With its excellent statistical capabilities and a huge package ecosystem, R supports transparent data analysis workflows with an emphasize on reproducible research. Geospatial R packages, such as sf, raster, and leaflet, enable complex geospatial studies and striking visualizations that facilitate gettting insights from geospatial datasets. Join us to learn how to use R to accesss, analyze, and visualize spatial data!Read more
CLIC-IT: Learning communities as innovation accelerator
Training: Introduction to Geospatial Raster and Vector with R
News and events on KiTeS LinkedIn page- Five workshops that boost your confidence in communication skills in a playful way
- Upcoming FMT Group Colloquia
Joint IACAP/AISB Conference on Philosophy of Computing and AI (IACAP/AISB-25)
Philosophy of Computing and AI Conference at UT in July 2025- Re-thinking biochemical sensors: imaging approaches to monitoring biomolecules in situ
PhD Defence Marieke Welle Donker-Kuijer | The Complexities of Simplicity - Examining Heuristic Expert Evaluation of Municipal Websites
PhD Defence Yoeko Mak | Flexible Robotic Endoscopes for Minimally Invasive Surgery Applications
Master final project presentation: Khoi Nguyen, Optimizing the Computational Efficiency of Fine-tuning and Inference for Large Language Models
Online information meeting parttime Master Public Management
