Submissions should be on graph-related topics that are technical in nature. They can include any stack, programming language, industry use case, technique, or methodology. Topics range from graph AI/ML projects to engineering and optimizations of the inner workings of applications.

There is no limitation on the types of use cases you can discuss. We do ask that presentations concentrate on the “how” – for example, showing the code, graph data models, Cypher queries, best practices, and lessons learned.

We strongly encourage first-time speakers and presenters from minority groups to submit proposals.

The three tracks of the conference are:

Building Intelligent Applications: APIs, Libraries, and Frameworks

Tools and best practices to create graph-powered applications with any software stack and programming language. Topics may include the open source development of frameworks and libraries for the graph ecosystem.

Machine Learning and AI

How graph technology provides context for your data and enhances the accuracy of ML and AI projects. Topics may include graph neural networks, responsible AI, graph embeddings, knowledge graph mining, and much more.

Visualization: Tools, Techniques, and Best Practices

Techniques and tools for exploring hidden and unexpected patterns in your data and presenting complex relationships. Topics may include knowledge graphs, ethical data practices, data representation, and much more.

We'll highlight some talks and speakers before the CFP deadline. Submit your abstract early for consideration.