Danni Tu, PhD
I am currently a data scientist/principal biostatistician at Regeneron, where I work on methods for digital health and wearable technology. Broadly, I am interested in answering questions about human health and disease through the lens of science and data. These questions naturally motivate the development of new statistical models for functions, networks, images, and other types of data with interesting high-dimensional structures.
In 2023, I completed a PhD in Biostatistics at the University of Pennsylvania, where I specialized in statistical and machine learning methods for brain (neuroimaging and neurocognitive) data, and where I was a part of the PennSIVE group. Prior to graduate school, I worked at Mathematica Policy Research.
Education
PhD, Biostatistics - University of Pennsylvania, 2023
MS, Biostatistics - University of Pennsylvania, 2020
BA, Mathematics - Princeton University, 2015
Research Interests
High-dimensional data (images, functions) from wearable devices, medical imaging, and digital health technologies
Graph theory and topological properties of complex neural systems
Machine learning and public policy
Skills
8+ years of research experience in statistical modeling and data science
Programming/development: R, Python, MATLAB, SAS, Stata, Java, Mathematica, Git, Bash scripting