His research centered on Bayesian inverse problems, in particular applications of hidden Markov models to geophysical data. As part of his PhD he also spent six months at UCSC, California, on topics related to stochastic optimization.

Everybody loves David. That is just the way it is, and we are the luckiest team to have him as a colleague.