Research within AI and Data Science
The Faculty of Engineering’s research in areas within artificial intelligence and data science contributes to smarter and visionary solutions for some of society’s biggest challenges.
We conduct interdisciplinary research in artificial intelligence and data science within the medical, energy, and optics sector, where we apply artificial intelligence and data science to improve procedures, provide information for decision makers and gain new knowledge. Our research focuses on design and development of novel AI models to address critical societal issues and facilitate future developments. This includes combination of statistical methods and artificial intelligence to provide explainable diagnosis and treatment solutions for patients and generating affordable and clean energy.
Research areas
Research specialties in Applied AI and Data Science are within artificial intelligence, data science and statistical signal processing, statistical machine learning, biostatistics, and epidemiology and our main research directions are mentioned here.
Artificial intelligence and health
AI has the power to change the way healthcare is delivered. It is arguably one of the biggest disrupting forces in healthcare when it comes to quality improvement, and it provides many new opportunities for innovative treatments. Finally, AI can support decision making, and enable faster diagnostics and treatment as well as more efficient workflows.
Big data analysis
Technological advancements have generated extensive structured, semi-structured, and unstructured data. The research units in the faculty of engineering focus on analyzing complex datasets to uncover hidden patterns, correlations, trends, and insights within the health, robotics, energy, and photonics domains. We aim to develop novel and innovative methods for analyzing data using statistics and artificial intelligence.
Classic artificial intelligence
The research units at the faculty of engineering also focus on classical artificial intelligence techniques. Our research focus includes but not limited to Logical inferences, Knowledge-based systems, Natural Language Processing, Neural network development, and Knowledge Representation and Reasoning within Health, Software technologies, and Robotics.
Virtual reality/Augmented reality
Interdisciplinary research from games to health, learning to robotics, data to code - in an environment designed for collaboration and technology-transfer. We aim to create experiences and technologies that enable people to shape and engage with the future.
Artificial intelligence and health
Big data analysis
Classic artificial intelligence
Virtual reality/Augmented reality
Last Updated 30.04.2025