Rex Zhitao Ying

Rex Zhitao Ying is an Assistant Professor in the Department of Computer Science at Yale University. His research interests include machine learning, optimization, and data science. Dr. Ying's work focuses on developing efficient algorithms for large-scale data analysis and applying these techniques to real-world problems. He is affiliated with the Yale University Computer Science department and contributes to academic research through his teaching and scholarly activities.

Rex (Zhitao) Ying is a researcher at Yale University specializing in graph learning, time series deep learning, geometric deep learning, foundation models, and multimodal systems. His work focuses on developing advanced methods for representation learning on graphs, with applications in recommender systems, molecular graph generation, and complex physics simulation. He has contributed to the design of graph neural networks, including differentiable pooling, hyperbolic graph convolutions, and explainability frameworks. His research also explores trustworthiness in large language models and natural language reasoning through first-order logic. Ying's publications highlight the intersection of graph theory, deep learning, and real-world applications.