Juan Sequeda

Juan Sequeda

Principal Scientist

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About this Speaker

Juan Sequeda is the Principal Scientist at data.world. He holds a PhD in Computer Science from The University of Texas at Austin. Juan's goal is to reliably create knowledge from inscrutable data. 

Juan is the recipient of the NSF Graduate Research Fellowship, received 2nd Place in the 2013 Semantic Web Challenge for his work on ConstituteProject.org, Best Student Research Paper at the 2014 International Semantic Web Conference (ISWC), the 2015 Best Transfer and Innovation Project awarded by the Institute for Applied Informatics and nominated two additional times for best paper at ISWC. Juan is on the Editorial Board of the Journal of Web Semantics, Advisory Board of Patterns Journal, member of multiple knowledge graph and AI program committees (ISWC, ESWC, WWW, AAAI, IJCAI), organizer of various academic and industry conferences and general chair of The Web Conference 2023. 

Juan’s research and industry work has been on designing and building Knowledge Graph for enterprise data integration. He has researched and developed technologies for semantic and graph data virtualization, graph data modeling, schema mapping and data integration methodologies. He pioneered technology to construct knowledge graphs from relational databases, resulting in W3C standards, research awards, patents, software and his startup Capsenta (acquired by data.world). Wearing his scientific hat, his research interests are at the intersection of Logic and Data for (ontology-based) data integration and semantic/graph data management. Wearing his business hat, Juan does business strategy, technical sales and works with customers to understand their problems to translate back to R&D. Juan strives to build bridges between academia and industry as the current co-chair of the LDBC Property Graph Schema Working Group, past member of the LDCB Graph Query Languages task force and standards editor at the World Wide Web Consortium (W3C). Juan is also the co-host of Catalog and Cocktails, an honest, no-bs, non-salesy podcast about enterprise data.

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