Learning olfactory models to support the perfume creation process

We will develop a data-driven methodology which will allow us to uncover the olfactory perception mechanisms related to perfume creation and exploit them to build rational solutions that improve product performance and differentiation. We will do so by designing and developing novel statistical learning algorithms that exploit side information to reliably learn olfactory models assessing product properties and qualities.