Jackson Loper works under the guidance of Liam Paninski and David Blei. His research produces analytical tools to understand datasets arising from new single cell experimental methods. These methods yield measurements for tens of thousands of features of a single cell, and researchers can measure the masses of cells in a single tissue. The result is a data matrix with hundreds of millions of entries. In which ways is it possible—or impossible—to use these kinds of measurements to understand the diversity within cell populations? That is the question he seeks to answer with his research, which also focuses on handling cases of missing data. The lack of data makes it fundamentally impossible to infer parameters for typical models and calls for new approaches such as his. Loper received a bachelor’s degree and Ph.D. in applied mathematics from Brown University.