In this webinar, Dr. Youjin Lee, an Assistant Professor in the Department of Immunology at the University of Pittsburgh, will share her laboratory’s approach to understanding how spatial context within tissues governs immune cell state, behavior, and function. Dr. Lee’s research centers on the development of single-cell spatial multi-omics technologies and computational modeling frameworks that enable high-resolution mapping of immune–tissue interactions in intact biological systems.
By integrating precision-cut tissue preparation with advanced spatial profiling and quantitative modeling, her work bridges experimental biology and data science to extract interpretable, predictive insights from complex tissue architectures. In this talk, Dr. Lee will discuss how spatially resolved single-cell data can be generated from precision-cut tissue samples, how tissue-level interactions can be modeled and interpreted, and how these datasets can be leveraged to train machine-learning models that capture emergent properties of tissue microenvironments.
Learning Objectives
In this webinar, Dr. Lee will:
– Describe how single-cell spatial data can be generated from precision-cut tissue
– Explain how spatial modeling approaches reveal tissue-level interactions
– Discuss how spatial datasets can be used to train machine-learning models for biological discovery