I am interested in bringing geometric methods to bear on non-parametric non-Euclidean methods, network inference and subsequent applications. Data often collectively lives in a space with interesting geometry or describes objects, like networks, with interesting geometry. My interest is in importing tools from differential geometry and analysis to extend non-parametric inference for both kinds of data. I am interested in applications ranging from imaging to social network analysis. 

Dena Asta joined the statistics faculty in 2015. She is also a member of the Translational Data Analytics. Her research has previously been funded by the NSF.