Rex (Zhitao) Ying is an assistant professor in the Department of Computer Science at Yale University. His research focus includes algorithms for graph neural networks, geometric embeddings and explainable models. Rex is the winner of the dissertation award in KDD 2022. He is also the author of many widely used GNN algorithms such as GraphSAGE, PinSAGE and GNNExplainer. In addition, Rex worked on a variety of applications of graph learning in physical simulations, social networks, knowledge graphs and biology.
What do you do with data science?
Rex developed the first billion-scale graph embedding services at Pinterest, and the graph-based anomaly detection algorithm at Amazon, and the first large-scale graph neural networks for subsurface simulation.
Rex is passionate about graph learning applications in social science, natural science and medicine. His interest lies in exploring and exploiting the relational information underlying the data, and use graph learning techniques to allow ML models to capture such information. His long-term vision is to create explainable, expressive, and scalable self-supervised domain specific models based on data from different modalities, and the extracted relational information within the data.