Speaker "Clair Sullivan" Details Back



Applying Machine Learning to Knowledge Graphs


In order to turn data into action we must know the context of that data. Traditionally humans were required to provide that context, however recently more and more context is available through data science approaches utilizing knowledge graphs. Knowledge graphs can be created in many different ways, which will be explored in this talk; we will particularly focus on the use of natural language processing (NLP) to generate a knowledge graph. With a knowledge graph in hand, we will then discuss how a variety of data science and machine learning methods can be used to achieve tasks such as entity resolution, label prediction, and link prediction between two unlinked nodes in the graph.
Who is this presentation for?
Practicing data scientists and machine learning engineers
Prerequisite knowledge:


Dr. Clair Sullivan is currently a graph data science advocate at Neo4j, working to expand the community of data scientists and machine learning engineers using graphs to solve challenging problems. She received her doctorate degree in nuclear engineering from the University of Michigan in 2002. After that, she began her career in nuclear emergency response at Los Alamos National Laboratory where her research involved signal processing of spectroscopic data. She spent 4 years working in the federal government on related subjects and returned to academic research in 2012 as an assistant professor in the Department of Nuclear, Plasma, and Radiological Engineering at the University of Illinois at Urbana-Champaign. While there, her research focused on using machine learning to analyze the data from large sensor networks. Deciding to focus more on machine learning, she accepted a job at GitHub as a machine learning engineer while maintaining adjunct assistant professor status at the University of Illinois. In 2021 she joined Neo4j as a Graph Data Science Advocate. Additionally, she founded a company, La Neige Analytics, whose purpose is to provide data science expertise to the ski industry. She has authored 4 book chapters, over 20 peer-reviewed papers, and more than 30 conference papers. Dr. Sullivan was the recipient of the DARPA Young Faculty Award in 2014 and the American Nuclear Society's Mary J. Oestmann Professional Women's Achievement Award in 2015.