Machine learning pervades almost every scientific and technological field today. SimulaMet develops novel methodologies and algorithmic solutions to address issues in society, for example within cancer, infertility and sports. The research is focused on mathematical foundations of machine learning, the experimental study of machine learning algorithms, and the application of machine learning in real-life applications.
Data Science and Knowledge Discovery
Advancing the frontiers of machine learning and data mining by developing novel methods and algorithms to analyse complex data sets and reveal underlying patterns.
Addresses real-world challenges in distributed systems, using a holistic approach that encompasses all components of the system as well as novel machine learning algorithms. Conducting basic research, experimental prototyping, and running experiments in the intended real-world environments.
Signal and Information Processing for Intelligent Systems
Delivers innovative solutions for intelligent and multimodal sensor networks, information systems, and networked cyber-physical systems, by creating theories and algorithms that blend the areas of signal processing, data science and machine learning.