Recent developments in machine learning approaches in chemometrics
Eugenio Alladio (Università degli Studi di Torino)
Friday 2nd February 13:00-14:00 Maths 311B
Abstract
The seminar will explore the transformative effect of statistical machine learning in the field of chemometrics, where an interdisciplinary approach at the intersection of chemistry, statistics and artificial intelligence is enabling scientists to gain insights from complex chemical datasets.
The seminar will provide an overview of the diverse applications of chemometrics and machine learning in various fields of chemistry. From deciphering intricate patterns in spectroscopy and chromatography data to advancing analytical chemistry methods, the integration of machine learning strategies is set to transform traditional approaches to data analysis and interpretation.
Cutting-edge chemometrics methods that use machine learning algorithms for predictive modeling, feature extraction and classification tasks will be described. Real-world examples and case studies will illustrate how these strategies contribute to improved decision-making processes, faster research results and the discovery of novel correlations in chemical datasets.
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