Joshua Cape

Joshua Cape 

Assistant Professor
Department of Statistics
University of Pittsburgh

E-mail: joshua DOT cape AT pitt DOT edu

1802 Wesley W. Posvar Hall
230 South Bouquet Street
Pittsburgh, PA 15260

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About

I am an Assistant Professor in the Department of Statistics at the University of Pittsburgh. I currently serve as an Associate Editor for the Journal of Statistical Planning and Inference. Previously, I spent one year as a National Science Foundation Mathematical Sciences Postdoctoral Research Fellow in the Department of Statistics at the University of Michigan. I completed my Ph.D. in Applied Mathematics and Statistics at Johns Hopkins University in Baltimore, Maryland.

My current research interests include:

— Statistical Machine Learning
— Multivariate Statistics
— Network Analysis
— Matrix Analysis

On the theoretical side, my research focuses on developing statistical theory for networks (graphs) and on examining the mathematical foundations of data science via the study of matrices. On the applied side, I work on problems arising in the natural sciences (currently, neuroscience and biology) and in the social sciences (currently, economics and sociology) that involve dimensionality reduction, inference, and structure discovery.

My research is supported by NSF grants DMS-1902755 and SES-1951005. I am grateful for past research support during my studies from the NSF, NIH, DARPA, and JHU. Any opinions, findings, and conclusions or recommendations are those of the author(s) and do not necessarily reflect the views of funding agencies.

Education

What's New

Upcoming and Recent Talks

Conference on Computational and Methodological Statistics       virtual       Dec. 2021
Joint Statistical Meetings       virtual       Aug. 2021
International Conference on Econometrics and Statistics       virtual       June 2021

Publications

Preprints may differ from published papers in terms of content and formatting.

Preprints

Teaching

Fall 2021  —  STAT 2221: Advanced Applied Multivariate Analysis  —  Canvas site