Gurus of Chemometrics

Introduced by Lutgarde Buydens, Professor of Analytical Chemistry, Dean Faculty of Science, Radboud University, Nijmegen, The Netherlands

In 2013 I penned a feature for The Analytical Scientist: “Towards Tsunami Resistant Chemometrics,” drawing attention to a paradox at the heart of data science: traditional methods, regarded as the cornerstones of chemometrics, were not designed to handle the large volumes of data available today. New methods and strategies were urgently required to extract relevant chemical information from the data tsunami.

More than half a decade on, the data analysis landscape has changed tremendously. In computer science, deep learning and artificial intelligence methods have emerged, whilst in mathematics there is a growing interest in investigating the fundamentals of data science. Together, this progress can only further benefit the chemometric field. This made me wonder: what is driving chemometricians, and how do they experience the field in relation to these developments? Asking some experienced chemometricians in key application areas such as food analysis, environmental science, metabolomics and industrial process analysis for their views on the field – and how they create value from analytical data – seemed a proper way to address this.