Computational Analytics and Intelligence (CAI)

The CAI research group at IFI investigates new ways of building intelligent computer systems for data analytics and intelligent systems with the goal to push the limits further in terms of scalability, efficiency, robustness, security, dependability, autonomy, and real-time capabilities.

This research group is mainly a special interest group offering an academic platform for members of all IFI research groups and research partners. Major goal is the 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.
As the group’s main focus is on systems research, application areas and mathematical and physical foundations are typically explored in close collaboration with experts from the respective disciplines. Health, biology, energy, climate, and society are domains the group is particularly interested in.

Research topics

  • System architectures for data capturing, managing, processing and real-time feedback
  • Scalable analytical systems for monitoring based on multimodal time series
  • Multimodal sensor network systems enabling distributed climate observatories
  • Detection of complex patterns in multidimensional spatial and temporal data
  • Visualization and exploration of large datasets to support hypothesis forming
  • Intelligent systems enabling critical event prediction at low false positive rates
  • Efficient big data analytical systems for biology and biomedicine
  • Computer aided detection (CADe) and diagnosis (CADx) systems in healthcare
  • Efficient artificial intelligence (AI) for cyber-physical systems (CPS) cognition, automation and optimization
  • Internet of Things (IoT) related analytics for environmentally friendly modes of transport

 

Selected 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
  • Sense services raw data analysis in the NUDGE project

 

Researchers

  • Alexander Horsch, Computer Science, CADe/CADx, Physical Activity
  • Anders Andersen, Computer Science, Open Distributed Systems
  • Hoai Phuong Ha, Computer Science, Arctic Green Computing
  • John Markus Bjørndalen, Computer Science, High Performance Distributed
  • Otto Anshus, Computer Science, High Performance Distributed Systems
  • Randi Karlsen, Computer Science, Open Distributed Systems
  • Weihai Yu, Computer Science, Open Distributed Systems
  • Bente Morseth, Comunity Medicine & Sport Sciences, Physical Activity
  • Michael Moreau, Department of Philosophy
  • Martin Rypdal, Department of Mathematics and Statistics
  • Puneet Sharma, Department of Engineering and Safety

 

Students

  • Håvard Thom, Computer Science, COAT Tools
  • Sigurd Beldo, Sport Sciences, Fit Futures, Physical Activity

 

Collaboration partners

  • UiT Computer Science Department, research groups AGC, HPDS, ODS
  • UiT Medical Faculty, research group “Physical Activity and Public Health”
  • Technical University Munich, Department of Computer Science
  • University of Cambridge, MRC Epidemiology Unit
  • German National Cohort (NaKo), Competence Unit 7-Days Accelerometry

This research group addresses Computer Science body of knowledge area Intelligent Systems 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