Ryan McComb on a tree-lined street

Who's behind Tessera

Hey, I'm Ryan.

I'm an elections nerd (not kinda; I really am :)). I built the DeepSky partisan estimator, which guesses how a precinct votes by looking at it from orbit, and I am very passionate about onion futures. I also do some data science at VoteHub, with a lot of other people who care about election data.

I built Tessera because it seemed like a fun thing to make. Redistricting is a puzzle I care about, and one that more compute can crack: the existing tools are slow, cumbersome and confusing, and I wanted to see how fast a Mac app built on Rust could get. I live in Evanston, Illinois. If you want to reach me, email me. (Actually, probably don't: I never check it. DM me on X.)

Under the hood

Tessera in brief

Draw and explore

A native Mac app with live district maps, 3D analysis, gerrymander experiments, reports and posters. Public maps cover every state, with 2024 presidential results where available, checked against certified totals.

Compare with neutral maps

An exact sequential Monte Carlo sampler in Rust (written by Claude, with me doing a very cursory code review and a lot of nodding). Its Metal GPU port runs about 100 times faster than redist in our benchmarks.

Find a better plan

Mosaic's annealed ReCom search, rewritten in Rust with the same scoring formulas. The optimizer runs 2.4 to 2.7 times faster in our tests on an M5 MacBook Air.

Credits

Tessera builds on Mosaic by Matt Mohn (MIT license), ReCom from the MGGG Redistricting Lab, and sequential Monte Carlo redistricting from Harvard's ALARM Project.

Map data comes from the U.S. Census Bureau (2020 Census, TIGER/Line), the Voting and Election Science Team (CC BY 4.0), the ALARM Project (CC BY-SA 4.0), and Dave's Redistricting (CC BY-SA 4.0). Where used, 2024 results from the Redistricting Data Hub and the New York Times retain their non-commercial terms.