It's completely mistaken to think that the NN craze means noone works on anything else. Academia has very many people researching whatever they want, full-time

It's completely mistaken to think that the NN craze means noone works on anything else. Academia has very many people researching whatever they want, full-time or on the side. AI has especially many veteran researchers stubbornly following long-standing lines of research which have unimpressive results. Noone can say they're wrong. Hinton was once that guy doing unfashionable research into NNs. Anyway, there are also memetic algorithms, which extend genetic algorithms by adding local search (some form of local improvement such as gradient following or simple handcoded heuristics) to the genetic global search. Actually a very simple idea (e.g. alternate mutation and/or recombination and optimisation steps). They tend to perform better than pure genetic algorithms because they can actually use gradient information or heuristics. It's a very broad class of algorithms which tend to have many hyperparameters.