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and not a single DS/ML person seems to have ever heard of it.

Because most folks in DS/ML are working on predicting likelihood to press a button. You don’t need Fourier transforms for that.

you do, depending on your feature preprocessing.

CNN is essentially a FT with learnable kernels.

well, it’s certainly usually convolution. Hardly anyone knows why or how that connects to the FT though.

Most DS/ML people are useless chimps.

FWIIW I've used it all the time, along with wavelets, cepstrums, lifters and Hilbert transforms. For timeseries with nonlinearities and lots of data points, it's the way to go. 9/10 times I'd rather hire a EE with signal processing background than a statistician or data scientist for time series work.

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