Chemometrics

Chemometrics is a highly interdisciplinary field closely related to analytical chemistry. It combines principles from chemistry, mathematics, statistics, and computer science to extract meaningful information from complex chemical datasets and enhance the utilization of chemical measurements. The integration of artificial intelligence techniques like deep learning methods further revolutionizes the field of chemometrics, expanding the applications of this discipline to numerous areas of analytical chemistry.

The range of possible topics for the section includes but is not limited to the following:

• Development of new statistical, mathematical and chemometrical methods as well as deep learning techniques for all branches of analytical chemistry.
• Novel applications of chemometrics to all areas of analytical chemistry, and typical domains of interest include experimental design, signal processing, supervised modelling, decision making, robust statistics, mixture analysis, multivariate calibration and analysis, principal component analysis, etc.
• Systematic evaluations of statistical, mathematical and chemometrical methods as well as deep learning techniques for all branches of analytical chemistry.