Dynamic Time Warping is a pretty neat application of dynamic programming that takes two time series and tries to squish one time series to look like the other, with some constraints that you can't do too much squishing. This is used a lot in speech recognition to normalize away variation like e.g. how long you spend on a vowel sound.