Master

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.

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

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.

Our Data-driven Service Innovation (DDSI) course challenged a class of motivated JADS students to assess and improve the current service offerings and business model of our industry partner, Datacation, using the knowledge they learned in class.

For her Master thesis Renée van Erp researched how the process of creating dose treatment plans for locally advanced left-sided breast cancer patients could be automated to be more efficient and less time consuming.

What could you do for sustainable cities if you drove a fleet of trucks with cameras through the city? That's how DPD Netherlands, Fruitpunch AI and JADS got to work on this open call for students.