It’s something called the Getis-Ord Lecture in Spatial Analysis, Fri 18 Feb 2022, 7:15pm NY time (the conf is in Arizona but I’ll be giving the talk remotely):

Understanding Spatial Models in Context

What do Vermonters think about gun control? Why did Charles Dickens’s plots have so many coincidences? What’s the Electoral College voting power of large and small states? Why is geology a surprisingly poor predictor of home radon levels? How can we figure out the parameters of a spatial smoother by pure thought? What all these examples have in common is that we can understand a statistical model by carefully mapping its assumptions to reality. This is always the case but especially so with spatial models with their often nonintuitive structure. Rather than attempt a general theory, we shall instead try to reach some understanding through a series of examples.