What We Work On
Our research is centered on Process Mining, Recommender Systems, and Applied AI, complemented by AI-Driven Process Innovation, Simulation & Digital Twins, and Predictive & Prescriptive Analytics.
Together, these areas enable us to understand complex processes, predict what happens next, recommend better actions, and develop intelligent solutions for real-world problems.
Process Mining
We develop methods to discover, analyze, predict, and improve real-world processes from event data, transforming operational data into actionable process intelligence.
- Object-centric process mining and process discovery
- Event abstraction, conformance checking, and predictive monitoring
- Process visualization, organizational mining, and process optimization
Recommender Systems
We develop personalized and context-aware recommendation technologies that help users make better choices, with a particular focus on the fashion industry.
- Personalized product, outfit, and fashion recommendation
- User preference and behavioral modeling
- Context-aware and AI-enhanced recommendation
Applied AI
We develop and apply AI and machine learning technologies to real-world problems, combining advanced models with domain knowledge and operational data.
- Generative AI, large language models, and AI agents
- Domain-specific foundation models
- Deep learning, multimodal AI, and explainable AI
AI-Driven Process Innovation
We combine process intelligence and AI to redesign how organizations operate, moving beyond process analysis toward intelligent and adaptive ways of working.
- AI-assisted process redesign and improvement
- Generative AI and agents for process innovation
- Human–AI collaboration and intelligent workflow automation
Simulation & Digital Twins
We build data-driven simulation models and digital twins to evaluate alternatives and improve complex systems before changes are implemented in the real world.
- Process digital twins and automated simulation modeling
- What-if analysis and scenario evaluation
- Applications in manufacturing and healthcare
Predictive & Prescriptive Analytics
We integrate prediction, optimization, and decision support to anticipate outcomes and determine what actions should be taken next.
- Process performance prediction
- Resource allocation and optimization
- Data-driven operational decision support
Application Domains
Our research is grounded in real-world challenges and strengthened through long-term collaboration with industry and public-sector partners.
Manufacturing
We apply process mining, AI, simulation, and optimization to semiconductor manufacturing, steel production, smart factories, and other complex manufacturing systems.
Healthcare
We develop process intelligence, predictive analytics, and digital twins for clinical pathways, hospital operations, patient flows, and healthcare decision support.
Fashion
We develop AI-powered recommender systems for personalized fashion services, including product recommendation, outfit recommendation, customer preference modeling, and intelligent curation.
From Data to Impact
Our research areas are deeply interconnected. We combine process mining with AI, predictions with optimization, process data with digital twins, and recommender systems with generative AI to address complex real-world problems.
Our goal is to move from data to understanding, prediction, recommendation, innovation, and measurable real-world impact.