Since the outbreak of the coronavirus, modellers from around the world have scrambled to predict the course of its spread, projecting forward from data on past infections and deaths in any region. Such estimates help public health officials and governments to judge the possible risks they face, and, on their basis, many nations have imposed […]

Random graphs can undergo structural phase transitions as a function of their model parameters. For example, in the well-known percolation transition, a network-spanning cluster of linked nodes abruptly appears at a critical value of the probability, c, for a link to exist between any pair of nodes.

Uncertain programs are optimization problems involving uncertainties in constraints or objectives. In the past few decades, such programs have been applied in areas from economics and management to automotive control and machine learning.

Policy makers in areas ranging from public health to weather forecasting or economics rely on mathematical models to inform their decisions. As models grow more complex and powerful, one might expect, they should contribute to better decisions.