We are a computational biology lab jointly located between the department of computer science and the computational medicine program. We develop new methods for automated, efficient, and unbiased analysis of immune profiling data, such as, flow cytometry, mass cytometry, and imaging mass cytometry. Our work specifically seeks to link particular immune cell-types and their functional responses to clinical or experimental phenotypes. Application areas of interest include, vaccine development, T-cell differentiation and designing more effective immunotherapies, neurodegenerative diseases, sexually transmitted diseases, and pregnancy. To design scalable and automated tools for these data, we develop and apply new methods using machine learning and graph signal processing.