This year again, Ondalys is sponsoring the 25th Chimiometrie Conference. Come and discuss with our team at this event.
2 occasions to discuss Chemometrics with our team !
February 17, 2026
Pre-conference courses
Come and attend the course which led by Dr Sylvie Roussel, an expert in Machine Learning and Chemometrics for more than 20 years, entitled :
Review of the main methods
of Machine Learning (ML)
She will provide an overview of the different Machine learning methods that can be used for the analysis of instrumental data. She will define the difference between Machine Learning and Chemometrics. And she will present several Machine Learning methods, such as Artificial Neural Networks (ANN), the Support Vector Machine Method (SVM), the Regression Trees methods (Classification and Regression Tree – CART) and Random Forests (RF);
February 18, 2026
Scientific oral
Jordane Poulain, Data Scientist, will present our latest work carried out in collaboration with the L’Oréal Research and Innovation Center and Synchrotron Soleil, on the theme :
Automated histological segmentation of hair follicles via hierarchical PLS-DA and FTIR hyperspectral imaging
This work aims to automate the identification of the different tissues composing the hair follicle using hyperspectral imaging in order to better assess the impact of cosmetic active ingredients on follicular health. The multivariate analysis of the data, based on hierarchical discrimination models (PLS_DA), has demonstrated its high relevance for the automatic segmentation of the different hair follicle tissues. This methodology offers a robust framework for future studies evaluating the molecular impact of cosmetic active ingredients on hair growth in each of the tissues that compose it.
The 2026 Chimiometrie congress is organized by the École Nationale Supérieure des Industries Chimiques (ENSIC) on the Grandville campus in downtown Nancy, France.
This annual meeting of industrial and academic scientifics interested in Chemometrics and data analytics will give our team the opportunity to share with you our expertise on the topics covered during the oral presentations:
- Spectroscopic data analysis,
- Hyperspectral imaging analysis,
- Design of Experiments – DoE
- OMICS data analysis (LC-MS, GC-MS, GCxGC, etc.),
- Process monitoring and optimisation
- and many other Chemometrics methods
More information soon
See more details on the Chimiometrie 2026 conference website.
The 2026 edition of the conference will be held in Nancy on the Grandville campus of the École Nationale Supérieure des Industries Chimiques (ENSIC).
Ondalys offers data analysis services and training and distributes some of the most widely used and recognized Chemometrics software, such as PLS_Toolbox® and SOLO® for Chemometrics, MIA Toolbox® for hyperspectral image analysis from EigenVector Research Inc., and Design-Expert® software from Stat-Ease for Design of Experiments.
The Chemometrics Art
At the heart of data analysis lies Chemometrics, a discipline that focuses on the complex relationships between different variables. In a context where data is vast and often intertwined, Chemometrics provides a powerful way to explore interactions between variables and discover those that have a significant impact on outcomes.
Rather than examining variables individually, Chemometrics seeks to capture the dynamics of interactions. This approach offers a holistic view of the data, uncovering hidden patterns and complex correlations.
By analyzing how variables interact with each other, Chemometrics makes it possible to identify those with the greatest influence on final results. These key variables may directly affect product quality, process performance, or other critical industrial metrics.
Chemometrics offers sophisticated techniques such as Principal Component Analysis (PCA), Partial Least Squares regression (PLS), and other advanced methods to unravel complex interactions. These approaches provide deeper insights into relationships between variables, thereby supporting better decisions and actions.
By integrating the art of Chemometrics into your industrial data analysis, raw datasets are transformed into actionable knowledge. By recognizing hidden influences and dependencies among variables, you can make informed decisions that drive your business toward efficiency and competitiveness.
