AI for Redistricting

I taught this for the first time in Spring 2024.  Students finished the course with a final project, analyzing a state/map of their choice.  Here is some sample student work:

North Carolina 2022 and 2023 Congressional Redistricting Map Analysis, by Qianru Wei and Mingda Ma

North Dakota Redistricting Analysis by Kushal Chekuri and Pedro Pinheiro

Here is an outline of the topics:

• Intro, Shape and population

  • Include graphs and dual graphs

• Metrics: eg, mean median, geo 

• Markov Chains and outlier analysis

  • What are MCs

  • MCs in redistricting: flip, recom 

  • Theory of MCs 

• Data wrangling

• Ecological Inference

• Short bursts

  • With finding VRA districts 

  • With testing metrics

• Extra topics (for example: GEO metric, Declination, the redistricting metagraph, machine learning to measure district compactness . . . )

• Project work