The important role of Data Science in our current time

Optimizing plant-based meat production with LiveKindly Collective

JADS collaborated with LiveKindly Collective to tackle a key challenge in the production of plant-based meat alternatives. This partnership, part of the EngD program, focused on optimizing the extrusion process—a critical step in achieving high-quality, consistent plant-based meat.

Automated reporting: Kortels' data integration with PowerBI

In collaboration with SME Datalab, Kortels implemented automated PowerBI dashboards to seamlessly integrate data from systems like Exact Online, SAP, and Microsoft Bookings. This innovation streamlined reporting processes, reduced manual effort, and provided real-time insights, enabling data-driven decision-making across the organization.

Advancing pear sorting with Arinze

JADS collaborated with Arinze on the Smart Pears project, using AI and robotics to sort pears with precision. Students tackled real-world challenges, advancing autonomous sorting systems and gaining hands-on experience in industrial data science applications.

Enabling product developers to perform portfolio optimization to easily reformulate food products

Unilever, a renowned global consumer goods company, is constantly innovating its food products to stay in sync with evolving factors. However, Unilever faces a significant hurdle.

AI-powered risk analysis: SME Datalab's collaboration with Safety Region Brabant North

In collaboration with SME Datalab, Safety Region Brabant North implemented Retrieval Augmented Generation (RAG) to swiftly gather factual data from public documents. This initiative reduced the time-intensive nature of risk analysis and minimized the risk of using incorrect information or leaking sensitive data.

Simplifying server cabinet configurations for Minkels.

Minkels, a division of Legrand, took proactive steps to support their growth ambitions by gaining in-depth insights into the configurations of sold server cabinets.

Exploring Exsell's data to build a recommender system

Exsell partnered with JADS in the Causal Inference course, presenting a real-world dataset challenge to students, to see what they did with it. The dataset was aimed at testing students' ability to build models and derive meaningful insights from the data

Enhancing government letter clarity with Machine Learning and ChatGPT

For her Master thesis Nadine Beks focused on using machine learning to improve letters from government sources like city councils and tax offices. She created and tested different models and found the GPT model was the most effective in making letters easier to understand.

Smarter screening for breast cancer

Stichting Yvya, together with EarlyWarningScan bv, is working with JADS to develop a new method of breast cancer screening that can also be used with young women, as opposed to mammography where screening is only possible for women after menopause.

"Dynamic pricing model for MTD: Using Web scraping to understand supply and demand better"

MTD's ambition is to develop a dynamic pricing model that calculates an optimal price based on event characteristics and MTD's expected available capacity on a given date. This will allow a more accurate response to predicted supply and demand during pricing discussions with clients.

Streamlining sales for MEG using Natural Language Processing

MEG's ambition was to speed up the sales process (customer request to final quote) by making their extensive product inventory more organized and transparent. The sales process could take up to 2 weeks due to the size and product preferences of the request, whereas MEG would like to give the customer a relevant offer right away.

Using NLP in streamlining document coding for DAS

DAS had a clear ambition to bring their historical dataset of 400,000+ legal documents up to date with a newly instituted coding scheme.
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