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Embedded Systems


Artificial Intelligence and Intelligent Systems

Foundational and applied research in Artificial Intelligence and Machine Learning for Intelligent Systems for both industry, medical and business applications. The research focuses on methods and techniques enabling learning, reasoning, experience reuse, and experience sharing. We work with both autonomous AI applications as well as decision support systems.

 

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To create intelligent behaviour in systems and services we use artificial intelligence including machine learning and reasoning, deep learning, data analysis, knowledge discovery, ontologies, domain knowledge, instance-based learning, deep learning, multi agent systems (MAS) to mention some of the methodologies and techniques. AI is today an essential "core" technology in many projects which is reflected in our broad collaboration with other groups, projects and universitys both national and international.

Research Focus:

  • Research on Machine Learning and Reasoning for a wide area of application in industry and health care for monitoring, classification, diagnostics, prediction and decision support.
  • Research on Data analysis, feature extraction and selection, data mining, and knowledge discovery
  • Research on Intelligent sensor, data fusion and sensor signal abstraction
  • Research on Big data to Smart data and Predictive analytics
  • Research on Distributed Artificial Intelligence and Machine Learning for Big data
  • Research on Deep learning for Image Processing and Computer Vision

Ongoing research projects

The goal of the TRUSTY project is to provide adaptation in the level of transparency to enhance the trustworthiness of AI-powered decisions in the context of remote digital towers (RDTs).


Project manager at MDU: Mobyen Uddin Ahmed

Main financing: EU, Sesear3 joint undertaking