Karl Rohe

Karl Rohe is a Professor of Statistics at the University of Wisconsin–Madison, with courtesy appointments in the School of Journalism and Mass Communication, Electrical & Computer Engineering, and Educational Psychology. His research focuses on modern data analysis challenges, including embeddings, PCA, and machine learning. He leads the Rohe Lab, which develops methods for network analysis and graph dimensionality estimation. Key contributions include the gdim package for estimating graph dimensions and work on spectral clustering. His work is supported by grants from the National Science Foundation (DMS-1309998, DMS-1612456, DMS-1916378) and the Army Research Office (W911NF-15-1-0423, W911NF-20-1-0051).

Research interests span post-modern data science, leveraging linear algebra for statistical methods, and applications in social networks. His lab’s GitHub repositories include implementations of algorithms like fastadi and invertiforms, reflecting his commitment to open-source software.