Congressional redistricting is dividing up a state into an assigned
number of districts, which will each hold independent elections and send
the plurality winner to Washington. Since districts are composed of
Census blocks, it’s exactly rephraseable as a graph partition problem on
a large but finite graph. Unfair or “gerrymandered” districts are bad
in some way (though opinions differ on exactly what way). So can’t we
just agree on the fairness metric and optimize? In my talks I’ll
explain some optimization perspectives on redistricting and I’ll argue
for where the interesting action is, including some open and
approachable real-world problems for you to explore. I’ll talk about
joint work with many collaborators in my lab, with an especially large
role played by Amariah Becker.
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