Research Focus
"Efficient Processing and Quality Management of Large-Scale Knowledge Graphs"
Abstract: Dr. Acosta’s research addresses the fundamental challenges of querying and maintaining integrity in distributed web data. Her work focuses on federated query processing and the assessment of data quality within Knowledge Graphs. By developing adaptive techniques for SPARQL query optimization and data cleaning, her contributions ensure that the decentralized "Web of Data" remains a reliable and efficient resource for both humans and AI agents.
Biography
Dr. Maribel Acosta is a Junior Professor of Databases and Information Systems at the Technical University of Munich (TUM), Germany. Before joining TUM, she was a postdoctoral researcher and PhD student at the Karlsruhe Institute of Technology (KIT), where she graduated with honors for her work on query processing over Linked Data.
She is a leading figure in the Semantic Web community, having served as a Program Committee Chair and track chair for major conferences like ISWC (International Semantic Web Conference) and ESWC. Her research interests lie at the intersection of Database Systems and Web Technologies, with a particular emphasis on query optimization, data quality, and the governance of large-scale knowledge bases. Dr. Acosta has received multiple awards for her research, including best paper nominations at prestigious international venues.