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Connecting the Knowledge Ecosystem Founded in 2019 at Columbia University, The Knowledge Graphs Conference is emerging as the premiere source of learning around knowledge graph technologies. We believe knowledge graphs are an underutilized yet essential force for solving complex societal challenges like climate change, democratizing access to knowledge and opportunity, and capturing business value made possible by the AI revolution.
KGC bridges the gap between industry, which is increasingly recognizing the necessity of integrated data, and academia, where semantic technologies have been developing for over twenty years. Our events, education, content, and community efforts facilitate meaningful exchange between diverse groups, and increase awareness, development and adoption of this powerful technology.
Conference – bridging the gap between research and industry
We organize workshops and tutorials to progress a number of Tech4Good themes, targeting objectives such as the United Nations Sustainable Development Goals and the development of a COVID-19 vaccine. At our most recent conference, 530 attendees participated, representing over thirty industries across forty-two countries. Speakers ranged from Bell Labs pioneer John Sowa to Morgan Stanley, AstraZeneca, and leading academics from Europe and USA. A variety of workshops and tutorials were also given, including several on tech4good themes–from the UN SDGs to personal health graphs and fake news.
KGC Vision and Values
Our goal is to build the community and become a leading source of learning around knowledge graphs.
We will achieve this by engaging and convening industry leaders and innovators, across sectors.
We will focus on the diversity of perspectives:
Professional Diversity: Industry practitioners, Business Users, Faculty, Scientists, Students
Gender & Age diversity
We will gather, share and publish content to increase learning.
We will build the community online and in-person through our content, meetups and conferences.
Live stream preview
Keshav Pingali | High Performance Knowledge Graph Computing On Katana Graph
Knowledge Graphs now power many applications across diverse industries such as FinTech, Pharma and Manufacturing. Data volumes are growing at a staggering rate, and graphs with hundreds of billions edges are not uncommon. Computations on such data sets include querying, analytics, pattern mining, and learning. In many use cases, it is necessary to combine these operations seamlessly to extract actionable intelligence as quickly as possible. Katana Graph is a start-up based in Austin and the Bay Area that is building a scale-out platform for seamless, high-performance computing on such graph data sets. We describe the key features of the Katana Graph Engine that enable high performance, and some important use cases for this technology from Katana's customers.
Bio: Keshav Pingali is the CEO of Katana Graph, a start-up in the area of graph computing backed by Intel Capital, Dell Technologies Capital, Redline Capital and Walden International, and a professor in the Department of Computer Science at the University of Texas at Austin where he holds the W.A."Tex" Moncrief Chair of Computing. He is a Foreign Member of the Academia Europeana, a Distinguished Alumnus of IIT Kanpur, India, and a Fellow of the ACM, IEEE and AAAS. He has served on the NSF CISE Advisory Committee (2009-2012), and he was co-Editor-in-Chief of the ACM Transactions on Programming Languages and Systems (2007-2010). He is the author of more 200 papers in the area of graph computing, parallel and distributed systems, and programming languages.