Gerrymandering has plagued the American electoral process since the country’s foundation, but has attracted increasing attention in recent years. By making elections uncompetitive, this practice has decreased voter engagement and trust in our democratic institutions. The goal of this SuperUROP project is to develop and implement an algorithm that can generate electoral districts with uniform probability on an electoral map. Such an algorithm would make it possible to characterize the distribution” of electoral maps. This could then serve as a tool to make statistical arguments in the courts about whether a given electoral map was gerrymandered. This would hopefully lead to the removal of these partisan maps and the use of maps drawn with less human bias.

I see SuperUROP as an opportunity to get meaningful experience as a researcher and gain very specialized expertise, specifically in the fields of graph algorithms and probability theory. Moreover, my project allows me to combine my passions for math and computer science and apply them to work on bringing positive change to this country. This is also a great opportunity to explore whether I would like to pursue a future in research.