Zoi Kaoudi

Zoi Kaoudi is an Associate Professor at the IT University of Copenhagen, affiliated with the Data, Systems, and Robotics school and the Data-intensive Systems and Applications department. Her research focuses on advancing data systems, knowledge graphs, and large-scale data analysis. She leads the Rank4QO project (2024–2027), funded by the Carlsberg Foundation, which explores query optimization using ranking algorithms.

Her work emphasizes machine learning integration in data management systems, including frameworks like Apache Wayang, which unifies diverse data analytics platforms. Key collaborations include projects with Volkswagen Group and SAP, addressing dynamic graph processing and knowledge graph embeddings.

Notable contributions include innovative approaches to parameter management (e.g., Good Intentions), automated data science pipelines (DORIAN), and efficient graph processing algorithms. Her recent publications (2023–2025) highlight advancements in machine learning systems, distributed data processing, and adaptive optimization techniques.

Current projects aim to bridge machine learning and data management through frameworks like Wayang and Dorian, with applications in air cargo revenue management and semantic web systems.