Data

Mathematicians are using topological abstractions to find places where it’s hard to vote.

Seventy years after the invention of a data structure called a hash table, theoreticians have found the most efficient possible configuration for it.

Alexei Efros has spent his career learning how machines see differently from humans. Now he’s helping to bridge the gap.

Cynthia Rudin wants machine learning models, responsible for increasingly important decisions, to show their work.

Arvind Narayanan uses quantitative methods to expose and correct the misuse of quantitative methods.

Built upon the ubiquitous Fourier transform, the mathematical tools known as wavelets allow unprecedented analysis and understanding of continuous signals.

Rediet Abebe uses the tools of theoretical computer science to understand pressing social problems — and try to fix them.

Most modeling efforts during the COVID-19 pandemic have sought to address urgent practical concerns. But some groups aim to bolster the theoretical underpinnings of that work instead.

In the fight against COVID-19, disease modelers have struggled against misunderstanding and misuse of their work. They have also come to realize how unready the state of modeling was for this pandemic.