2026 Kowalski Prize

Quality at the Universitat Politècnica de València (UPV), has been awarded the 2026 Kowalski Prize for his paper "Dynamic multiblock regression for process modelling", co-authored with Marco Cattaldo, a PhD graduate of the UPV, and Ingrid Måge, a researcher at the Norwegian Institute of Food, Fisheries and Aquaculture Research (NOFIMA), as part of the DIGIFOODS project.

With a prize of 500 dollars, the Kowalski Prize is one of the most prestigious awards in the field of chemometrics. It has the name Bruce R. Kowalski, one of the founding fathers of modern chemometrics and founding editor of the Journal of Chemometrics, a publication which awards a prize held in high esteem within the scientific community for its recognition of significant advances—both methodological and applied—in multivariate data analysis, statistics, machine learning and related fields applied to chemistry and process science.

How can we make joint use of information from different sensors, stages or data sources whose relationships evolve?

"Our paper," explains Alberto J. Ferrer Riquelme, "addresses a very common problem in industry: how to make joint use of information from different sensors, stages or data sources whose relationships evolve to better understand a process and predict its behaviour."

"To this end," he adds, "we have developed new tools that not only maintain a high predictive capacity but also help to identify which information is truly relevant and how changes over time influence it. This enables us to build simpler, more transparent and more useful models to support decision-making and the improvement of industrial processes," he states.

First Spaniard to obtain it in the last 15 years and third ever

By obtaining the prize, Alberto Ferrer becomes the third Spaniard ever to be included on the list of winners of an award that previously featured only two other Spanish researchers, Anna de Juan and Romà Tauler, who were recognised in 2009.

"For us," notes the UPV Professor, "this award is an incentive to continue highlighting the tremendous opportunities that multivariate statistical methods offer for solving real-world problems with a significant impact on improving quality, safety and productivity in industry and, consequently, in society."

Upcoming challenges

As Professor Ferrer acknowledges, "we are currently continuing to carry out research into multivariate statistical techniques combined with machine learning algorithms to generate interpretable models that aid decision-making, and so that we can transfer these to society through our two UPV spin-offs: Kenko Imalytics, which specialises in developing imaging biomarkers to aid in the diagnosis and monitoring of cancer, and Kensight Solutions, which focuses on consultancy and the development of data analysis software to improve industrial processes".

Box Medal 2025

Winner of the Box Medal – an award presented by the European Network for Business and Industrial Statistics (ENBIS) – exactly one year ago, Alberto Ferrer trained as an agricultural engineer at the UPV, where he then obtained a PhD in Statistics under the supervision of Professor Rafael Romero-Villafranca, one of Spain's leading industrial statisticians.

Ferrer Riquelme subsequently furthered his academic training abroad as a visiting lecturer at McMaster University, where he met Professor John F. MacGregor, who was also awarded the Box Medal in 2014.

Alberto Ferrer currently heads the Multivariate Statistical Engineering Research Group (GIEM-UPV), which focuses on the research and development of multivariate statistical techniques to improve process quality and productivity, as well as on the analysis of large data structures.