Uzay Kaymak

Uzay Kaymak is a Full Professor and Chair of Information Systems in Health Care at Eindhoven University of Technology (TU/e), with concurrent appointments at JADS Den Bosch, EAISI Foundational, and EAISI Health. His work bridges computational intelligence and healthcare, developing adaptive decision support systems through linguistic-numerical data fusion.

His educational background includes:

• MSc in Electrical Engineering (1992, Delft University of Technology)
• Chartered Designer Degree in Information Technology (1995)
• PhD in Control Engineering (1998, Delft University of Technology)

Research Interests:
Professor Kaymak pioneers computational intelligence frameworks integrating fuzzy set theory with machine learning for intelligent decision support. His work spans data/process mining, reinforcement learning, and clinical decision modeling, with applications in financial systems, economic analysis, and healthcare. Recent focus includes serious games for diabetes management and AI-driven water infrastructure monitoring, emphasizing model interpretability and real-world implementation.

Publication Trends:
His 2023-2025 output reveals intensified focus on environmental AI applications (water systems, desalination) and healthcare informatics. Publications demonstrate consistent integration of fuzzy logic with deep learning for interpretable models, particularly in leak detection, river monitoring, and clinical alert systems. The work shows strong industry-academia collaboration with practical implementations in Dutch hospitals and water utilities.

Scientific Awards:

• Best Industrial Paper Award (2020)
• Best Student Paper Award (2019)

Advising and Grants:
With 91 supervised students, Professor Kaymak leads major EU-funded projects including SmartDATA (2020-2025) for AI in connected systems, DiaGame (2019-2025) for diabetes self-management games, and GOAL (2018-2021) for gamified active lifestyles. His Eurostars project PADS pioneered reinforcement learning for programmatic advertising, securing significant industry partnerships with Shell and healthcare institutions.

Labs and Teams:
He co-leads the EAISI Health initiative and TU/e's Clinical Informatics program, collaborating with Jheronimus Academy of Data Science (JADS) and Zhejiang University. His interdisciplinary team combines AI researchers, clinical informaticians, and environmental engineers to develop deployable solutions for UN Sustainable Development Goals in health and clean water.