Population annealing is a generalized-ensemble Monte Carlo simulation algorithm that proves useful for the simulation of systems with complex free-energy landscapes and that offers superior parallelizability properties. As a meta-algorithm, population annealing can be combined with a wide range of simulation methods, including Monte Carlo and molecular dynamics. In the past, we have analyzed the approach regarding the scaling of statistical and systematic errors, proposed improvements and implemented the method on highly-efficient graphics processing units. More recent developments discussed at the MATRIX program regard the optimal choice of the resampling protocol and the combination of several population annealing simulations using weighted averages, as well as a combination of population annealing with quantum Monte Carlo simulations.