Readers, fear not! The rumors of my blog’s demise have been greatly exaggerated.

I have returned to announce the publication of my first scholarly article. It is “Porchlight: An Accessible and Interactive Aid in Preprocessing of Spectral Data”, which can be read on the Journal of Chemical Education at It is the culmination of nearly two years of effort after this application was first conceived, and many iterations since then have seen it transform from a little MATLAB tool to a proper and useful application.

The Porchlight GUI, but this time with noisy Raman data.

It’s a jaunty little read, so please inflate my ego and my viewing statistics. It’s freely accessible, so there’s no excuse.

On a more serious note, I think preprocessing is an important yet neglected topic. In a sense, calling it preprocessing is a misnomer as common practice is to revisit preprocessing after analysis to improve your results. I won’t belabor the point and repeat what’s already in the article, but here’s two topics I didn’t expand on in the article. One is that I like the work people have begun to try to automate preprocessing, there’s a few cited in my paper. I don’t know if this will be appropriate in most cases, but maybe if it’s simple enough it would help researchers get out of the rut of using the same methods every time. Two, I would keep an eye on the recent interest in applying deep learning/neural network models to either eschew the preprocessing step entirely for predictive model generation, or to use deep learning models to perform preprocessing. Again, it’s cool and interesting and I look forward to seeing these topics grow, but part of me is still concerned about ignoring the fundamentals of spectroscopy and treating spectra as black boxes of statistical data.

Anyways, I hope the spectroscopy and education communities find my contribution useful, and I hope that Porchlight helps us properly explore the impact of preprocessing on our spectra.