In the AI∙ML team, we have a strong focus on collaboration - both internally and externally. The team is involved in numerous national and international research projects in the field of artificial intelligence and machine learning.

Maintaining and fostering these collaborations enhances quality and impact of our research. 

Below you find a list of both current and completed research projects, as well as networks and partnerships in which we are involved.  

Contact and collaborate with us


Current Projects

Flexible Energy Denmark (FED) 

Flexible Energy Denmark (FED) is a Danish digitization project aimed at turning Danish electricity consumption flexible to enable excess power production from wind turbines and solar cells.

  • Partners: 24 partners representing Danish universities, utilities, companies and municipalities.
  • Funding: Innovation Foundation Denmark.
  • Project period: 2019-2023


Flexible Energy Production, Demand and Storage-based Virtual Power Plants for Electricity Markets and Resilient DSO Operation (FEVER)

The European Research & Innovation project FEVER aims at demonstrating and implementing solutions that leverage the potential of flexibility in generation, consumption and storage of electricity. 

  • Partners: Seventeen partners from eight European countries
  • Funding:  European Union's Horizon 2020 research and innovation programme.
  • Project period: 2020-2023

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CLAIRE - Controlling water in an urban environment 

In the project CLAIRE, researchers from Aalborg University attempt to improve the possibilities for understanding and controlling water in urban areas. The aim is to make certain the water does not end up in the wrong place at the wrong time.

  • Partners: Department of Computer Science and Department of the Built Environment, Aalborg University
  • Funding: The project is funded by the VILLUM FOUNDATION 

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VILLUM Investigator S4OS Scalable analysis of safe, Small and Secure Strategies for Cyber-Physical Systems

In our daily lives, We are surrounded by cyber-physical systems. These systems comprise software and hardware components communicating with and controlling a physical reality. They include wind turbines, cars and objects as critical as pacemakers. In these systems, the use of machine learning is very widespread.

However, the use of machine learning also leads to challenges that may have fatal consequences. Professor Kim Guldstrand Larsen and research leader of DEIS has received a DKK 30 million Villum Investigator grant for a project aiming to ensure that cyber-physical systems meet requirements concerning reliability and safety to a much higher degree than is the case today. 

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Verifiable and Safe AI for Autonomous Systems

The rapidly growing application of machine learning techniques in Cyber-Physical Systems leads to better solutions and products in terms of adaptability, performance, efficiency, functionality and usability. However, Cyber-Physical Systems are often safety critical, and the resulting need for verification against potentially fatal accidents is self-evident and of key importance.

The research aim of this project is to develop methods and tools that will enable industry to automatically synthesise correct-by-construction and near-optimal controllers for safety critical systems within a variety of domains.

  • Partners: ITU, Grundfos, HOFOR, Seluxit and Aarhus Vand
  • Funding: Innovation Fund Denmark
  • Project period: 2021-2024

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Researchers across Aalborg University will collaborate on mapping more bacterial genomes.

Data Science Meets Microbial Dark Matter

Bacteria are present everywhere. They can make us ill. They can keep us healthy. In other words, bacteria have an endless range of applications. But if we are to utilize this potential to the full, we need to know a much larger part of the genome of bacteria. And therein lies the catch: Today, we know the genome of far less than one percent of bacteria in nature. 

In this project researchers pool their knowledge on DNA sequencing, graph analysis and machine learning for mapping more bacterial genomes faster.

  • Partners: Department of Chemistry and Bioscience and the Department of Computer Science, Aalborg University 
  • Funding: The project is funded by the VILLUM FOUNDATION 
  • Project period: 2021-2022

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Read more about the DREAMS project

Digitally supported Environmental  Assessment for Sustainable Development Goals (DREAMS)

The vision of this project is to promote progress on Sustainable Development Goals (SDGs) by digitally transforming the way society accesses and communicates information about environmental impacts of projects and plans, in order to enable the best  decisions towards green transition in a transparent and inclusive democratic process.

  • Partners:15 Danish partners 
  • Funding: The project is funded by Innovation Fund Denmark
  • Project period: 2020-2023

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Read more about the project


Renewable energy generation and electrification are among the top priorities all over the world. An essential part of renewable energy generation is power electronics (PE) that perform electrical energy conversion. 

In this project, researchers combine AI and energy research to design and develop power electronics that can adapt to dynamic operation settings and predict failures.

  • Partners: Department of Computer Science and Department of Energy Technology, Aalborg University
  • Funding: The project is funded by the VILLUM FOUNDATION.
  • Period: 2020-2022

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Centres, Networks and Partnerships

Find more information about the Center for Data-Intensive Cyber-Physical Systems (DiCyPS)

Center for Data-Intensive Cyber-Physical Systems (DiCyPS)


Center for Data-Intensive Cyber-Physical Systems (DiCyPS) focuses on utilizing software and data from the IT management of complex physical systems for the development of smarter and more user-friendly solutions for society and individuals.

The competences of the center a.o. include experts within embedded software, Big Data and usability, who collaborate with researchers worldwide.

  • Funding: The research center is funded by Innovation Fund Denmark.

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Read more about the IT4BI Doctoral College

Erasmus Mundus Joint Doctorate in Information Technologies for Business Intelligence – Doctoral College

Since its inception 20 years ago, Business Intelligence (BI) has become a huge industrial domain and a major economic driver, and it encompasses many scientific and technological fields.

The Erasmus Mundus Joint Doctorate in Information Technologies for Business Intelligence – Doctoral College (IT4BI-DC) is designed to develop research excellence in this broad scope of fields. Its main objective is to train computer scientists who understand and help develop the strategies of modern enterprise decision makers.

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Completed projects

Read more about the QWeb project

Querying the Web of Data easily and efficiently (QWEB)

Ever since the Internet came into existence, it has been a goal to make information available and accessible free of charge. In the past couple of years, we have witnessed the growing popularity of the Open Data movement and Semantic Web technologies, which have finally made large amounts of data available -- forming the Web of Data. But we are still missing technologies that actually make efficient use of it. Hence, the main goal of the now-completed project QWeb was to develop breakthrough technologies based on Semantic Web standards, such as RDF and SPARQL, that overcome this gap and answer user queries easily and efficiently over the Web of Data.

  • Funding: The project was funded by the Danish Council for Independent Research (DFF) 
  • Period: 2015-2019

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Read more about the GOFLEX project

Generalized Operational FLEXibility for Integrating Renewables in the Distribution Grid (GOFLEX)

The GOFLEX project aimed at increasing the integration of renewables by applying smart grid technologies to make existing energy flexibilities usable for the grid.

The core element of the "GOFLEX technology” is an integrated platform of hard- and soft-ware building blocks, which are connected via open interfaces. The solution has been tested in a number of European demonstration sites, involving over 400 prosumers from industry, buildings and transport. 

GOFLEX was the forerunner of the FEVER project

  • Partners: 12 European partners
  • Funding: The project received  funding from the European Union's Horizon 2020 research and innovation programme
  • Project period: 2016-2020

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