Monthly Archives: February 2018
Within this project we seek to develop machine learning methods for the modelling of pathological human locomotion. This is a collaborative Sinergia project funded by the Swiss National Science Foundation.
OrbiLoc is an Innosuisse project in which the Data Mining and Machine Learning (DMML) group collaborates with the company Orbiwise. The goal of this project is to improve the localization accuracy achieved by IoT devices utilizing the LoRa network of Orbiwise. In the context of this project, DMML introduces machine learning techniques for localization, achieving significant performance improvements, having as a baseline the trilateration method currently used by Orbiwise. The percentage of improvement of the localization accuracy achieved so far lays in the range of 30%-55%, depending on the environment of the deployment.
SMELL is an Innosuisse project undertaken with collabration with the company Firmenich. The goal of the project is to 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 designed and developed novel machine learning algorithms that exploit side information to reliably predic olfaction of the product and exploit the similarities of ingredients with respect to olfaction.