- New Methods in Machine Learning: This page includes several projects suggesting ways to apply and extend state-of-the-art machine learning techniques, many with the aim of improving performance at practical industry applications.
- Hybrid Models Combining Machine Learning and Physical Knowledge: The aim in these projects is to combine machine learning and physical knowledge in order to obtain models that are relevant for industry. Sintef has two use cases with industrial partners on predictive maintenance for wind turbines and on virtual flow meters on the Valhall oil platform.
- Optimization and Learning for Warehouse Logistics: This project aims to improve human working conditions and reduce environmental and economic cost across the wholesale warehouse value chain by developing analytic and learning based algorithms for internal warehouse optimization problems.
Applied Machine Learning with Sintef
Sintef has a number of master projects involving applications of Machine Learning. We have previously had good collaborations with them supervising ROBIN-students on related topics. Contact Kai Olav Ellefsen if you have questions/ are interested in the projects below.
Publisert 28. sep. 2022 09:00
- Sist endret 28. sep. 2022 09:01