Short Bio

Koumudi Ganepola is a first-year PhD student and university assistant at the Database and Artificial Intelligence research unit at TU Wien.

She earned her bachelor’s in computer science and engineering (2020) from University of Moratuwa (Sri Lanka) and her master’s degree in Big Data Management and Analytics (2024) through the highly selective Erasmus Mundus Joint Master’s program. As part of her master’s program, she studied at several leading European institutions, Université Libre de Bruxelles (Belgium), Universitat Politècnica de Catalunya (Spain) and CentraleSupélec (France). She completed her master’s thesis on Frequent Pattern Mining for Tourist Behavior Analysis using Large Graphs at De Vinci Research Center, Paris.

PhD Project - Provenance in Evolving Knowledge Graphs

Supervised by Katja Hose

Koumudi’s research focuses on Provenance of Knowledge Graphs, particularly exploring how provenance can be integrated and utilized in evolving knowledge graphs. Her research aims to enhance the explainability and reproducibility of graph queries and inference processes by tracing the computational steps that lead to the derivation of facts or patterns within graph-based knowledge. This would enable precise tracking of data transformations and ensure data integrity in evolving knowledge graph environments.