Roberto Todeschini is currently Professor ad honorem at the University of Milano-Bicocca. Since the mid-1980s his research interests have focused on chemometrics and its applications in analytical chemistry and QSAR (Quantitative Structure–Activity Relationships). In the early 1990s, he founded the Milano Chemometrics and QSAR Research Group. His scientific output includes more than 250 publications. Among his most notable works are Handbook of Molecular Descriptors (R. Todeschini and V. Consonni, Wiley-VCH, 2000), and its later edition, Molecular Descriptors for Chemoinformatics (R. Todeschini, V. Consonni, Wiley-VCH, 2009).

He has always been a promoter and organizer of events, workshops, schools, and international conferences in the field of chemometrics. He served two terms as Coordinator of the Chemometrics Division of the Analytical Chemistry Division of the Italian Chemical Society and, in 2004, was among the founders of the International Academy of Mathematical Chemistry, of which he served as President for five years, from 2008 to 2013.

Marina Cocchi is at present Full Professor of Analytical Chemistry at University of Modena and Reggio Emilia. She has published more than 140 papers in international journals and books, covering a range of topics embracing Multivariate, Multi-way and Multiset methods; Data Fusion; 2D WT in Multivariate Images Analysis for fault detection and pattern recognition; algorithms for features selection in Wavelet Domain; Multivariate Statistical Process Control (MSPC); Food Authenticity; Chemical fingerprinting by spectroscopy (MIR, NIR, NMR, Raman) and chromatography. She has been in the board of Italian Chemometrics Group from 2001 to 2015, acting as President in 2007-11. Since 2010 she has been member of the editorial board of Chemometrics and Intelligent Laboratory Systems. She has been Editor of the book Data Fusion: Methods and Applications, Data Handling in Science and Technology series, vol.31, Elsevier 2019.

Age K. Smilde is emeritus professor of Biosystems Data Analysis at the University of Amsterdam. After having received his PhD (1990) in Analytical Chemistry/Chemometrics at the University of Groningen, he spent a year visiting Bruce Kowalski at the CPAC in Seattle (1992). After that, he became professor of Process Analysis at the University of Amsterdam (1993). In 2005, he moved with his research group to the Swammerdam Institute for Life Sciences (SILS) and became professor of Biosystems Data Analysis. During his scientific career, he held many part-time positions (AUMC, TNO, University of Copenhagen and Simula) where he broadened his expertise in different fields. During his years at SILS, his group has been working on metabolomics, systems biology and multi-omics data fusion. After his retirement (December 2023), he is still a bit active in research but besides that, he is focusing on his main hobbies: hiking in the mountains, playing music and philosophy.   

Evrim Acar is a Chief Research Scientist and the Head of Data Science and Knowledge Discovery Department at Simula Metropolitan Center for Digital Engineering (Oslo, Norway). She holds a PhD and an M.S. in Computer Science from Rensselaer Polytechnic Institute (Troy, NY), and a B.S. in Computer Engineering from Bogazici University (Istanbul, Turkey). Her research focuses on data mining methods, in particular, tensor factorizations, and multimodal data mining using coupled factorizations of higher-order tensors and matrices, as well as their applications in diverse disciplines. Prior to joining Simula, Evrim was a faculty member at the University of Copenhagen (Denmark), and a postdoctoral researcher at Sandia National Labs (Livermore, CA). She is currently serving on the editorial board of SIAM Journal on Matrix Analysis and Applications (SIMAX). She has also served as an Associate Editor of the IEEE Transactions on Signal Processing and held various positions in signal processing, data mining and numerical linear algebra communities.

Cyril Ruckebusch is full-professor at Polytech Lille - University of Lille and Editor-in-Chief of Journal of Chemometrics. His research interests are related to chemometrics in spectral imaging and time-resolved spectroscopy, inverse problems, image restoration, spectral unmixing and multivariate curve resolution. Current research focuses on developing new workflows for faster data acquisition and unmixing in microscopy for biomedical applications.

Julia Culzoni is Principal Researcher at CONICET and is a professor of Analytical Chemistry at the Faculty of Biochemistry and Biological Sciences at the National University of the Littoral (FBCB-UNL), Argentina. Since 2016, she has served as the Head of the Laboratory of Analytical Development and Chemometrics (LADAQ) at FBCB-UNL.

In 2018, she received the Estímulo en Ciencias Químicas Award from the National Academy of Exact, Physical, and Natural Sciences of Argentina. In 2021, she was honored with Special Recognition in the Emerging Leader category of the Mujeres Latinoamericanas en Química Award, presented by the American Chemical Society (ACS) and the Latin American Federation of Chemical Societies (FLAQ).

She has published 73 scientific papers in scientific journals focused on analytical chemistry and chemometrics. She currently supervises doctoral and postdoctoral fellows, as well as a researcher affiliated with CONICET.

Joaquim Jaumot is Research Scientist at the Institute of Environmental Assessment and Water Research, Spanish National Research Council (IDAEA-CSIC). His research lies at the interface of chemometrics, analytical chemistry, and environmental omics. He develops and applies advanced multivariate data analysis methods, particularly multivariate curve resolution–derived approaches, to extract meaningful chemical and biological information from complex systems. His recent work focuses on spatial omics, integrating chemometric strategies to explore molecular and spatial organization in environmental and toxicological studies. Through algorithm and software development, he aims to bridge experimental and computational approaches, enabling a more interpretable and data-driven understanding of environmental and biological processes. He has authored over 85 scientific papers and several software tools that are widely used across disciplines, fostering collaborations among analytical chemistry, molecular biology, and environmental sciences.

Marena Manley is a researcher and academic in Food Science at Stellenbosch University (SU), where she has been a full professor since 2010. She completed her PhD in 1995 at the University of Plymouth (United Kingdom), where her engagement with near-infrared (NIR) spectroscopy began. Following 18 months in industry with FOSS, she joined Stellenbosch University in 1997, when she initiated research using and applying NIR spectroscopy and later introduced NIR hyperspectral imaging in the mid-2000s. Her research group was among the first internationally to publish cereal-related hyperspectral imaging studies.

She has supervised more than 95 postgraduate students. Her publication record includes over 135 peer-reviewed papers, one book and several invited book chapters. Her research, while rooted in grain quality and functionality, has expanded to diverse food systems – including honey adulteration, sourdough fermentation, chocolate refining, and gummy candy formulation. Her scientific achievements are reflected in multiple awards, including the SU Chancellor’s Award for Research (2022), the International Tomas Hirschfeld Award (2025) in recognition of her contribution to NIR spectroscopy, and most recently an SU’s Research and Innovation Excellence Award in the Established Researcher category (2025). She serves on the Board of the South African Academy of Science and Arts and is currently the co-chair of the 22nd International Diffuse Reflectance Conference (IDRC), to be held in Knoxville, Tennessee, in July 2026.

Sergey Kucheryavskiy is an Associate Professor in the Department of Chemistry and Bioscience at Aalborg University, Denmark. He received his PhD in Physics and Mathematics in 2001 and then took a break from research for a couple of years. In 2004 he began rebooting his career and decided to shift his research interests toward chemometrics. He has been gradually developing his career as a chemometrician since then. His current research areas include chemometrics (both theoretical and applied), vibrational spectroscopy, image analysis, and scientific programming. In his spare time, Sergey works on pet projects that result in various packages, apps, and toolboxes for using, teaching, and learning chemometrics and related disciplines. The results of these activities can be found at https://mda.tools

Åsmund Rinnan is an Associate Professor in Exploratory Data Analysis in the Department of Food Science at the University of Copenhagen (Denmark). He is also Head of the Cross-sectional Group of Chemometrics and Machine Learning and member of the Food Proteins Group. He is an expert in development of multivariate data analysis with internationally recognized scholarship in chemometrics and spectroscopy. His research explains how processing and storage induced chemical changes of food can be understood through the combination of multivariate data analysis with spectroscopy, especially fluorescence. His data analytical approach is based on the use of domain knowledge (expert knowledge about the system) to unfold the hidden information in large datasets. He uses this knowledge to develop predictive models for optimizing food processing and storage conditions in collaboration with other research groups and the food industry to improve food quality and support more sustainable food production.

Barbara Giussani is an Associate Professor of Analytical Chemistry at the University of Insubria (Italy), where she teaches Analytical Chemistry and Chemometrics to both Bachelor and Master students, as well as doctoral candidates.

Her research focuses on the development of smart analytical methodologies for the direct analysis of real-world samples requiring minimal or no pre-treatment. Her analytical expertise lies primarily in portable spectroscopic techniques, applied both in field measurements and in process control. She combines a statistical design of experiments (DoE) approach with multivariate data analysis, ranging from the study of multivariate error structures to the development of exploratory, predictive, and classification models. Recently, her work has also focused on enhancing the interpretation of multivariate models through figures of merit and performance indicators to improve model reliability and analytical significance. All her methods are developed and validated on real case studies, in collaboration with several Italian and international research institutions. Her research spans multiple domains, including materials science, food sciences, cultural heritage, and multivariate process monitoring and control.