Researcher in machine learning for industrial applications, hybrid AI (data driven modelling of physical systems), combining machine learning and optimization, explainable AI, data science and statistical analysis.
Working on overcoming challenges for implementing machine learning and artificial intelligence in a range of very different industrial settings where physics play a role and data is less than perfect.
Education
PhD in astrophysics from Dark Cosmology Centre, Niels Bohr Institute, University of Copenhagen, 2009
Competence and research areas
- Machine learning for industrial applications
- Hybrid AI: Data driven modelling of physical systems
- Explainable AI
- Combining optimization and machine learning
- Data science and statistical analysis
- Construction sector, energy sector, logistics
- Predictive maintenance
- Teaching and continued education
Linkedin
https://www.linkedin.com/in/signe-riemer-s%C3%B8rensen/
ResearchGate
https://www.researchgate.net/profile/Signe-Riemer-Sorensen
ORCID
https://orcid.org/0000-0002-5308-7651
