Graphs are widely used to model complex data nowadays: social networks, recommendation engines, computer networks, bio-informatics, to name a few. Graph theory has traditionally been a core area of research in computer science and artificial intelligence. With the growing number of applications and amount of data, Graph Computing addresses the storage, analysis, synthesis, and processing of (possibly large) graphs to solve complex problems in industry applications.

​TOPICS OF INTEREST​​ include, but are not limited to:
- Graph algorithms for industry applications
- Fundamentals of graph computing including storage of graphs,
- Graph databases, query languages, query optimization, integrity and security,
- Graph OLAP, graph mining, graph learning, graph reduction, and graph visualization.
- Knowledge graphs
- Network analysis
- Big graph analytics
- Integration and platforms