Biography. Paul Groth is Professor of Algorithmic Data Science at the University of Amsterdam where he leads the Intelligent Data Engineering Lab (INDElab) and is scientific director of the UvA’s Data Science Center. He holds a Ph.D. in Computer Science from the University of Southampton (2007) and has done research at the University of Southern California, the Vrije Universiteit Amsterdam and Elsevier Labs. His research focuses on intelligent systems for dealing with large amounts of diverse contextualized data with a particular focus on web and science applications. This includes research in data provenance, data integration and knowledge sharing.

Previously, Paul led the design of a number of large scale data integration and knowledge graph construction efforts in the biomedical domain. Paul was co-chair of the W3C Provenance Working Group that created a standard for data provenance interchange. He has also contributed to the emergence of community initiatives to build a better scholarly data ecosystem including altmetrics and the FAIR data principles. Paul is co-author of “Provenance: an Introduction to PROV” and “The Semantic Web Primer: 3rd Edition” as well as numerous academic articles. You can find him on twitter: @pgroth . 

Biography. Fabian M. Suchanek is a full professor at the Institut Polytechnique de Paris in France. He obtained his doctorate at the Max-Planck Institute for Computer Science in Germany. In his thesis, Fabian developed the YAGO knowledge base, one of the largest public knowledge bases, which earned him an honorable mention of the SIGMOD thesis prize, as well as, 10 years later, the “Test of Time” of The Web Conference 2018. Fabian was a postdoctoral fellow at Microsoft Research in Silicon Valley and at INRIA Saclay. Then he led a research group at the Max-Planck Institute for Computer Science. In 2013, he became an associate professor, and in 2016 a full professor at Télécom Paris, now part of Institut Polytechnique de Paris. With his students, Fabian works on natural language processing, neuro-symbolic reasoning, information extraction, rule mining, and knowledge graph management. He has published over 100 scientific papers, and his work has been cited over 19,000 times.

Biography. Claudia d’Amato is associate professor at the University of Bari – Computer Science Department and she got the Italian Habilitation for the functions of Full Professor for the Scientific Sector “Information Processing Systems” and "Informatics”. She obtained her PhD in 2007 from the University of Bari, Italy. She pioneered the research on Machine Learning methods for ontology mining and Knowledge Graphs that represents her main research interest jointly with the development of neural-symbolic and explainable solutions to be applied to Knowledge Graphs. Claudia d’Amato has been also invited researcher at several universities and international research institutes such as: the University of Koblenz-Landau in 2006, 2007, 2008, 2013 with Prof. Stefen Staab, the University of Oxford in 2012 working with Prof. Thomas Lukasiewicz, INRIA –Sophia-Antipolis in 2015 working with Dr. Fabien Gandon and Prof. Andrea Tettamanzi, the University of Poznan in 2011 and 2013 working with Dr. Agnieszka Lawrynowicz, FBK in 2012 working with Dr. Luciano Serafini. She is member of the editorial board of the Transactions on Graph Data and Knowledge (TGDK) journal, the Neurosymbolic Artificial Intelligence Journal, the Semantic Web Journal and the Journal of Web Semantics. She served as General Chair for ISWC 2022, Program Chair for ISWC 2017, ESWC 2014, Vice-Chair for ISWC 2009, Journal Track chair for TheWebConf 2018 (previously WWW), Tutorial Chair for ECAI 2020, Workshop and Tutorial Chair for ESWC 2026, Machine Learning Track Chair for ESWC’12-’13-’16-’17 and PhD Symposium chair at ESWC’15-’21 and at ISWC’23. She served/is serving as a PC member of a number of international conferences in the area of Artificial Intelligence, Machine Learning and Semantic Web such as AAAI, IJCAI, ECAI, ECML, ISWC, TheWebConf, ESWC.

Biography.