Speaker: Ernesto Jimenez-Ruiz (City, University of London).

Tabular data in the form of CSV files is the common input format in a data analytics pipeline. However, a lack of understanding of the semantic structure and meaning of the content may hinder the data analytics process.  Thus, gaining this semantic understanding will be very valuable for data integration, data cleaning, data mining, machine learning and knowledge discovery tasks. At the same time, organizing and integrating disparate resources into a knowledge graph will enhance the access to data and enable the application of machine learning techniques over graph data (e.g., knowledge graph embedding approaches).

Bio: Ernesto Jimenez Ruiz is a Lecturer in Artificial Intelligence at City, University of London affiliated to the Research Centers for Machine Learning and Artificial Intelligence. He is also a researcher in the Centre for Scalable Data Access (SIRIUS) at the University of Oslo, Norway and a visiting researcher at The Alan Turing Institute (UK). He previously held a Senior Research Associate position at The Alan Turing Institute and a Research Assistant position at the University of Oxford. His home university (Universitat Jaume I, Castellon, Spain) awarded a “Premio extraordinario de doctorado” (roughly translated as a Extraordinary Doctoral Award) to his doctoral thesis (Engineering category 2010-2011). His research has covered several areas, including bio-medical information processing and integration, ontology reuse, ontology versioning and evolution, ontology alignment. His current research interests focus on the application of Semantic Technology to Data Science workflows and the combination of Knowledge Representation and Machine Learning techniques.

Transmissão em direto via Zoom (password: 666314).