Founded in 2000 as a small team focused on preference modelling and fuzzy set theory, KERMIT (an acronym for “Knowledge Extraction, Representation and Management using Intelligent Techniques”) has grown into a leading research unit shaping the future of intelligent techniques and their applications. Over time, KERMIT evolved into a comprehensive team spanning all stages from data analysis to decision-making, with a focus on knowledge-based, predictive and spatio-temporal modelling paradigms. By maintaining a unique balance between theoretical advancements and practical applications, KERMIT has achieved remarkable success in output, visibility, and recognition. To accommodate growing specialization and enhance its reach, three subunits officially branched off in 2024: BionamiX, BioML and Biovism. Despite this structural evolution, KERMIT remains dedicated to its holistic philosophy, integrating diverse disciplines to tackle complex challenges.

KERMIT’s mission is to harness mathematics and computation to unravel life's complexities, optimize biological functions, and drive innovation in biodesign and decision-making under uncertainty. Focused on applied biological sciences—including biotechnology, environmental technology, plant breeding and food technology—, KERMIT refines existing methods and develops cutting-edge approaches across disciplines. The team is committed to creating accessible software tools that transform data streams into actionable and interpretable insights. Valuing continuous learning, interdisciplinary collaboration, and mental well-being, KERMIT embraces a holistic approach to solving challenges in our data-driven, interconnected world.

Mathematical modelling at KERMIT emphasizes intuitively appealing, rule-based paradigms—such as fuzzy modelling, cellular automata, and formal concept analysis—as well as cross-fertilizations thereof. The team has a particular interest in exploring the underutilized diversity of underlying mathematical structures and functions, contributing significantly to the foundations of order theory, uncertainty modelling and aggregation theory. Computational modelling at KERMIT is dedicated to developing and applying cutting-edge techniques—such as differentiable, probabilistic, and evolutionary computation—to enhance the understanding and engineering of biological systems. By integrating AI-driven simulations, the team bridges the gap between theoretical models and real-world applications.

On February 5, 2026, Lixuan An successfully defended her Ph.D. thesis "Analysis of exceedance patterns in distributional tails based on Extreme Value Theory" and was awarded the title of Doctor of Bioscience Engineering: Mathematical Modelling. Lixuan was supervised by Bernard De Baets and Stijn Luca. The research of Lixuan was supported by the China Scholarship Council and Bijzonder Onderzoeksfonds van Universiteit Gent.