Three of my open-source projects

I also contribute actively to open-source software, both within and outside my professional roles. Over the years, I have maintained several projects; below are two long-term packages that I have led and continuously developed for more than a decade.

prospectr

Author and maintainer (since 2013)

prospectr is an R package for the processing, pre-processing, and calibration sample selection of visible and near-infrared (vis–NIR) spectroscopic data. It provides a comprehensive set of utilities to support spectral data analysis workflows, from signal transformation and filtering to representative sampling of large spectral libraries.

The package is widely used in chemometrics and spectroscopy research (with more than 500 citations in scientific journals) and is designed for performance and scalability. Core functions are optimised for speed, including implementations based on C++ via Rcpp, enabling efficient use on large datasets commonly encountered in industrial and research applications.

Documentation and vignettes: https://cran.r-project.org/web/packages/prospectr/vignettes/prospectr.html

Github repository: https://github.com/l-ramirez-lopez/prospectr

resemble

Author and maintainer (since 2014)

resemble is an R package for local modelling, similarity-based learning, and domain adaptation in spectral chemometrics. It includes mbl() for memory-based learning with on-the-fly local models, liblex() for retrieval-based prediction using libraries of local experts, and gesearch() for evolutionary subset selection of reference samples relevant to a target domain. The ideas behind these methods had been developing in my work for years: liblex traces back to around 2019, and my work on evolutionary search began around 2020, partly inspired by Lobsey’s earlier work. Early internal versions of these methods were extensively explored in industrial applications before becoming part of the package.

CRAN documentation and vignettes: https://cran.r-project.org/web/packages/resemble/index.html

Package websiste: https://l-ramirez-lopez.github.io/resemble/

Github repository: https://github.com/l-ramirez-lopez/resemble

proximetricsR

Author and maintainer (since 2020)

proximetricsR is an R package for building, validating and deploying near-infrared calibration models in instruments. It covers the full workflow: reading spectral and reference data, preprocessing, PLS calibration with cross-validation, validation diagnostics including Mahalanobis (GH) distance and spectral residuals, model reporting, and serialisation of models to the instrument’s native format.

Development began in 2020. The package was used internally at my work for several years and was made publicly available in 2026.

CRAN documentation and vignettes: https://cran.r-project.org/package=proximetricsR
Package website: https://proximetricsr.r.packages.buchi-nir.io/
GitHub repository: https://github.com/buchi-labortechnik-ag/proximetricsr/