Knowledge Graph day will be on April 30.

Knowledge graph (KG) is the backbone to enable cognitive Artificial Intelligence (AI) which depends on cognitive computing and semantic reasoning. Knowledge graph is the connected data with semantically enriched context. It is the crucial step for the next moves of AI, no matter whether the AI revolution is in designing novel deep learning algorithms or solving pressing real-world problems. Gartner predicted that knowledge graph application and graph mining will grow 100% annually to enable more complex and adaptive data science. Graph convolutional neural networks, graph transformer, graph embedding and more have achieved great performance on various downstream tasks. As the size of knowledge graph is growing exponentially, scalable graph solutions are key to store, process, and empower graph AI methods on these large-scale knowledge graphs. Furthermore, explainability, fairness, and stability of graph deep learning methods become unavoidable to enable transparent and fair decision making. Knowledge Graph day will be the main venue to bring top notch speakers from industry and academia, and create the great networking opportunities for audiences with diverse backgrounds.

Knowledge Graph Day Schedule (April 30)
Location: Zlotnik Ballroom section 6 at AT&T Center
8:00-8:10	Welcome by Chairs
8:10-8:35	Chaitan Baru (NSF)
8:35-9:00	Sergio Baranzini (UCSF)
9:00-9:25	Oshani W Seneviratne (RPI)
9:25-9:50	Tyler Derr (Vanderbilt)
9:50-10:15	Yizhou Sun (UCLA)
10:15-10:45	Break
10:45-11:10	Stefan Decker (Aachen)
11:10-11:35	Xia "Ben" Hu (Rice University)
11:35-12:30	Panel: KG in Academia (Moderator: Sergio Baranzini)
12:30-1:45	Lunch Break
1:45-2:10	Charlotte Nelson (Mate Bioservices)
2:10-2:35	Keshav Pingali (katana Graph)
2:35-3:00	Lingfei Wu (Pinterest)
3:00-3:30	Break
3:30-3:55	Jeff Dalton (Bloomberg/Glasgow)
3:55-4:30	Panel: KG in industry (Moderator: Ying Ding)