Christopher Geoga received his bachelor’s degrees in mathematics and statistics from the University of Chicago in 2016. He is interested in modeling and inverse problems for processes with sophisticated dependence structure across time and space, approximate dense linear algebra and fast algorithms, and spectral domain representations of covariance structure and nonstationarity.

Research interests

• Spatial and spatiotemporal statistics
• Scientific computing
• Integral equationsgrabowsh
• State-space models

Projects:
MACSER