Complex mechatronic products such as cars, airplanes, engineering machinery etc. usually have a large number of variants. Each variant is specified by configuration rules. In cars, every single component in average affects 90% of the other ~50,000 components. It takes tens of thousands of such configuration rules to map these relationships.
A knowledge-based representation of product configuration rules allows a high performant AI-based rule satisfiability analysis.
M.Sc. Mechanical Engineering
Deloitte
https://www.deloitte.com
Boris worked at Deloitte for three years and is responsible for business development and application of semantic technologies @ Deloitte. He developed concepts and impemented semantic applicaitons for multiple automotive OEMs and suppliers as BMW, Porsche, Daimler, Toyota, VARTA, BSH and other.
Knowledge Graphs (KGs) have been recognized by several industries as an efficient approach for data governance, semantic enrichment, and as a data integration technology that brings unstructured and structured data together. One of the paramount processes, which determines the usability of your KG over the years, is the process of the KG enrichment and curation.
PhD
Semantic Web Company
http://www.semantic-web.at/
Tomas Knap works as a software engineer and research at Semantic Web Company. Tomas obtained his master's and PhD degree in informatics at Charles University in Prague, Czech Republic. His PhD investigations are dedicated to the trustworthiness of Linked Data integration and consumption.
