In my research, I focus on the entire pipeline of data-driven applications, from data engineering and management to knowledge engineering and the use of AI and analytics in different application domains. The effective application of analytics and AI in real-world applications depends on the availability of high-quality data, the selection of appropriate analytical methods, and the responsible deployment of developed systems. Likewise, operational systems also require high-quality data for proper functioning. Accordingly, my research focuses on the development of scalable data management approaches for AI applications, data-driven and knowledge-based decision-making and optimization methods, and trustworthy AI and analytics.

An important part of my work focuses on application-oriented basic research with real-world impact in different domains.

High-quality data for effective AI and analytics requires an appropriate data infrastructure. In this regard, I'm investigating the use of multi-dimensional contextualized knowledge representation in connection with the concept of the data lakehouse to build scalable data infrastructure for operational and analytical purposes.