About
Data Science Leuven has been running monthly meetups in Leuven for years. 3,956 members, 650 reviews averaging 4.5 stars, and a consistent format that works: two to three practitioner talks on data science and machine learning topics, followed by drinks at STUKcafé next door. The 77th edition runs on 20 May 2026 at the Arenberginstituut inside STUK on Naamsestraat.
DSL talks range across the full data and ML spectrum — ML engineering, production data pipelines, analytics, NLP, computer vision, business applications. The audience is a mix of Leuven-area practitioners, students, and academics. It is one of the most consistent and well-attended data communities in Belgium.
Speakers for this edition are to be announced. If you want to speak, the organising team takes submissions via Sessionize year-round.
Programme
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19:00
Doors open — STUK Arenberginstituut, room 02.C004
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19:30
Talks begin — speakers to be announced
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21:00
Beers at STUKcafé — Naamsestraat 96
Speakers
Speakers for the 77th edition have not been announced yet. Check the Meetup page for updates, or submit a talk proposal via Sessionize.
Submit a talk › sessionize.com/data-science-leuvenWhat DSL Talks Are Usually About
ML Engineering in Production
A recurring theme at Data Science Leuven is the distance between data science as it is taught and data science as it is practised in production environments. Talks in this vein explore the pipeline work that happens after a model is trained: feature engineering at scale, model serving infrastructure, monitoring and drift detection, retraining schedules, and the organisational dynamics of getting ML systems into product. If you work with data professionally, these are often the most directly useful sessions.
Applied NLP
Leuven has a dense NLP research community at KU Leuven (DTAI group, CompLing group, HCI group), and DSL frequently features talks that bridge research and application: question answering systems, document classification pipelines, entity extraction in domain-specific corpora, and increasingly the practical application of LLMs in enterprise contexts — what actually works in production, prompt engineering limitations, fine-tuning vs. RAG trade-offs.
Data Infrastructure and Analytics Engineering
The analytics engineering layer — the work of modelling, testing, and serving clean data within organisations — has become a recognised engineering discipline in its own right over the past several years, largely driven by tools like dbt. DSL talks in this area cover data warehouse architecture, data modelling practices, the analytics engineering workflow, and the organisational changes that happen when analysts take ownership of the transformation layer. Practical, opinionated, and relevant to anyone building data products.
Computer Vision in Industry
Belgium has a significant manufacturing sector, and KU Leuven has strong research groups in computer vision. DSL regularly features talks on practical computer vision applications: quality inspection systems, object detection and tracking in logistics, defect classification using deep learning, and the emerging field of vision-language models applied to industrial contexts. Less academic than KU Leuven seminars, more grounded in what works when you have a deployment deadline.
Attend
Organised by
Kris Peeters
Organizer, Data Science Leuven. Has been running the community since its early meetups.
Sam Debruyn
Co-organizer, Data Science Leuven. Data engineer and community builder in the Belgian data ecosystem.
Meetup profile ›Michael Tandecki
Co-organizer, Data Science Leuven.