Center for Artificial Intelligence (CAI)

The Center for Artificial Intelligence, CAI, at IFI investigates new ways of building intelligent computer systems and autonomous intelligent systems, using, among many techniques data analytics, decision-support, and decision-making with reasoning, with the goal to push the limits further in terms of scalability, efficiency, robustness, security, dependability, autonomy, and real-time capabilities.

Center for Artificial Intelligence includes AI areas and fields, such as Computational Analytics and Intelligence and cybernetics, and conducts research enabling scientific discoveries by applying algorithms to identify patterns and anomalies in data, test hypotheses, create models, and quantify uncertainties. Artificial Intelligence is about software systems that resemble human intelligence or act as human beings while performing tasks and that can reason, execute plans and perform striving towards autonomous decision-making and actions.
CAI research group conducts research within machine intelligence and artificial intelligence in a broad sense providing many opportunities for research collaboration and innovation. As the group’s main focus is research on systems and application areas, mathematical models and physical aspects are typically explored in close collaboration with experts from the respective disciplines: manufacturing (Industry 4.0), health, biology, energy, and society are domains the group is particularly interested in. This research group is a part of the Open Distributed Systems group and is led by Prof Anne Håkansson.
CAI is also a special interest group offering an academic platform for members of all other IFI research groups and research partners. As a platform, CAI supports in-depth discussion of challenges related to analytical systems IFI researchers face in their projects, in order to create synergies and increase research impact and success.

Research topics

  • System architectures for data capturing, managing, processing and real-time feedback
  • Efficient artificial intelligence (AI) for cyber-physical systems (CPS) cognition, automation and optimization
  • Scalable analytical systems for monitoring based on multimodal time series
  • Multimodal sensor network systems enabling distributed health observatories
  • Detection of complex patterns in multidimensional spatial and temporal data
  • Visualization and exploration of heterogeneous datasets
  • Intelligent systems enabling critical event predictions
  • Efficient big data analytical systems
  • Internet of Things (IoT) and Cyber-Physical System (CPS ) related analytics for different infrastructures, i.e., health, manufacturing, transportation, energy, buildings and different environmental matters

Selected projects

  • Robust systems: Robust decision-making in autonomous cyber-physical systems
  • Sense services raw data analysis in the NUDGE project
  • VirtualStain: AI solutions to virtually stain label-free cell and tissue images for studying cardiovascular diseases of fish and mammals
  • OrganVision: Real-time visualizing and modelling of fundamental process in living organoids towards new insights into organ-specific health, disease, and recovery
  • IDUN - from PhD to professor: Gender balance in top research positions at the Faculty of Information Technology and Electrical Engineering

Connected projects

  • Physical activity research in Fit Futures, Tromsø Study, German National Cohort
  • Sensor-based distributed arctic observatory in COAT Tools
  • Energy informatics research in the ARC center for renewable energy


  • Anne Håkansson, Computer Science, Artificial Intelligence AI
  • Dilip Prasad, Computer Science, Bio-AI
  • Alexander Horsch, Computer Science, Bio-AI, CADe/CADx, Physical Activity
  • Randi Karlsen, Computer Science, Open Distributed Systems
  • Anders Andersen, Computer Science, Open Distributed Systems
  • Weihai Yu, Computer Science, Open Distributed Systems

 PhD students:

  • Rohit Agarwal Computer Science, Bio-AI
  • Yigit Can Dundar, Computer Science, Artificial Intelligence AI
  • Abhinanda Punnakkal, Computer Science, Bio-AI
  • Ayush Somani, Computer Science, Bio-AI
  • Muhammad Sulaiman Computer Science, Artificial Intelligence AI



  • Bernt Arild Bremdal, Computer Science and Computational Engineering, UIT Narvik.
  • Chiara Bordin, Computer Science, Arctic Green Computing, IFI, UIT Tromsø
  • Hoai Phuong Ha, Computer Science, Arctic Green Computing, IFI, UIT Tromsø
  • Aya Saad, Enigneering Cybernetics, NTNU, Trondheim
  • Sameline Grimsgaard, Samfunnsmedisin,  UIT Tromsø
  • John Markus Bjørndalen, Computer Science, Cyber-Physical Systems, IFI, UIT Tromsø
  • Otto Anshus, Computer Science, Cyber-Physical Systems, IFI, UIT Tromsø


  • UiT Computer Science Department, research groups ODS, CPS, AGC,
  • UiT Medical Faculty, research group “Physical Activity and Public Health”
  • Department of Engineering Cybernetics, NTNU
  • Technical University Munich, Department of Computer Science

This research group addresses the Computer Science body of Artificial Intelligence defined as "the study of solutions for problems that are difficult or impractical to solve with traditional methods [...] The solutions [...] deal with sensing (e.g. speech recognition, natural language understanding, computer vision), problem-solving (e.g., search, planning), and acting (e.g., robotics) and the architectures needed to support them (e.g., agents, multi-agents)." ACM/IEEE, 2013


Research groups at Department of Computer Science:

Arctic Green Computing (AGC)

Computational Analytics and Intelligence (CAI)

Cyber-Physical Systems (CPS)

Cyber Security Group (CSG)

Health Data Lab (HDL)

Health Informatics & -Technology (HIT)

Open Distributed Systems (ODS)