From Structures to Vectors: Decoding How Knowledge Graph Characteristics Shape Embedding Strategies
Project Partners
Vienna University of Economics and Business
Marta Sabou
Principal Investigator
Prof. Dr. Marta Sabou is a Full Professor for "Information Systems and Business Engineering" at the WU. She focuses on research at the intersection of Semantic Web technologies and Human Computation and Crowdsourcing. She is an accomplished academic (over 100 peer-reviewed papers, h-index=45) and has extensive project work and management experience.
Fajar J. Ekaputra
WP4 Lead
Dr. Fajar J. Ekaputra is an Assistant Professor at the WU on the topic of Semantic Web for Knowledge Engineering and Knowledge Management. He has a vast research project experience on the topic of the Semantic Web and its applications in several domains, including Industrie 4.0, Smart Cities, Smart Grid, and Personal Data management.
Majlinda Llugiqi
WP1 Lead
Majlinda Llugiqi is a PhD student at the University of Business and Economics (WU), Vienna, Austria. She earned her Master’s degree in Logic and Computation from the Technical University (TU) of Vienna. Her research focuses on Neuro-Symbolic AI, knowledge graphs, machine learning, and knowledge engineering..
Vienna University of Technology
Databases and Artificial Intelligence
Katja Hose
Co-PI
Prof. Katja Hose is a Full professor at TU Wien's, heading the Data Management and Knowledge-Driven AI (DMKI) Lab. Previously, she was a professor at Aalborg University, a postdoc at the Max Planck Institute for Informatics, and received her PhD in Computer Science from Ilmenau University of Technology. Her research spans data and knowledge engineering, graph data management, knowledge graphs, querying, analytics, and machine learning, with extensive interdisciplinary collaborations in bioscience, health, and environmental assessment.
Emanuel Salinger
Co-PI
Professor Emanuel Sallinger is a full professor at TU Wien in the Databases and Artificial Intelligence Group and Vice Dean for Business Informatics and Data Science. He leads the Knowledge Graph Lab, funded by the Vienna Science and Technology Fund (WWTF). Previously, he was a Senior Researcher at the University of Oxford, where he still lectures on Knowledge Graphs and Databases.
His research centers on Knowledge Graphs, spanning theoretical foundations and scalable AI systems. His widely cited work has significantly influenced data management, knowledge representation, and logic-based AI.
Eleonora Laurenza
WP3 Lead
Eleonora is a senior post-doctoral researcher in Databases and Artificial Intelligence at TU Wien . Her main focus is on neuro-symbolic methods for Knowledge Graphs and reasoning. I particular, she is currently investigating expressive and actionable representations of logic-based/semantic KGs. In the past, she worked as an Innovation Manager and Researcher at the Central Bank of Italy, contributing to research-intensive projects on Financial Knowledge Graphs.
Milos Jovanovik
WP2 Lead
Dr. Milos Jovanovik is a Postdoctoral Researcher in the Databases and Artificial Intelligence Group at TU Wien, Austria. He is also an Associate Professor in Computer Science and Engineering at the Ss. Cyril and Methodius University in Skopje, N. Macedonia. His expertise lies in Knowledge Graphs and knowledge-driven AI, with a focus on semantic data modeling, constraint-based graph generation, and graph-based reasoning for analytics and decision support.
Nader Sobhi
Nader Sobhi is a PhD student at TU Wien in the DMKI group. He earned his Master's degree from the VU Amsterdam where he worked on Knowledge Graph Embdding compression and graph algorithms for finding Terminal Strongly Connected Components in two separate projects. His research focuses graph algorithms as well as Knowledge Graphs and their embedding methods.
Hesham Morgan
Hesham Morgan is a master's student at TU Wien in the Databases and Artificial Intelligence (DBAI) group. He is currently working on his master's thesis under the supervision of Prof. Emanuel Sallinger. His research focuses on knowledge graph embedding methods, with particular interest in improving model expressiveness while maintaining computational efficiency. His broader research interests include knowledge graphs, logic, graph theory, and mathematical optimization.