Geometry for Social Good
summary
Uses persistent homology to detect urban growth and climate “tipping points” and applies this to epidemic spread, with a concrete example of positioning resources during the 2018 Ebola wave in DR Congo. Uses Forman-Ricci curvature to find clumped regions of networks where prices or infections concentrate and to time interventions. Uses generative AI (mentions OpenAI and NightCafe) to produce culturally relevant campaign images. Publishes Python and R code and points to existing PH packages for reproducible workflows.
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chapters (9)
- 0:00Introduction
- 1:10Geometry tools for social good
- 3:17Urban growth and climate change
- 4:43Epidemic response and allocation
- 5:48Food insecurity and modeling
- 7:11Network interventions for behavior
- 7:31Generative AI in public health
- 10:44Representation in data and tech
- 12:10Resources and learning
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