Jan Tore Sanner besøker AI-laben

Scientific coordinators

Heri Ramampiaro
Scientific Coordinator – NTNU
 Heri Ramampiaro
Sigmund Akselsen
Scientific Coordinator – Telenor
 Sigmund Akselsen



The AI lab aims at addressing the following factors for making the AI education and research at NTNU even more efficient and contributing to society development at large:

  1. More resources for research, teaching and supervision at NTNU to accommodate the growth in interest in machine learning and AI.
  2. Better access to real datasets to accommodate professors and students in performing the actual work.
  3. Input on real operational problems that can be solved by Analytics, Machine Learning, and AI, and problem owners using that input in practice.
  4. High visibility of world class research and development in AI, Machine Learning and Big Data Analytics to attract talents from inside and outside Norway, and ultimately create new jobs in the country.


Telenor Group is one of the world's major mobile operators, with 211 million consolidated mobile subscriptions. Telenor Group has mobile operations in 13 markets in the Nordic region, Central and Eastern Europe and in Asia. To deliver on the ambitions of growth and value creation Telenor will take the position as customers' favorite partner in digital life. To reach the ambition as a Digital Service Provider, knowledge within AI and Big Data Analytics will play a key role in Telenor's strategy going forward.

The Department of Computer Science (IDI) at the Faculty of Information Technology and Electrical Engineering (IE) is the host department for the AI lab. The lab involves other departments at NTNU with activities in this area.

Telenor Research will be the main contact point in Telenor, and the lab will be closely linked to ongoing research and development activities in Telenor.


Lab facilities are populated by (processed) data from Telenor and other collaborating partners. In addition we will make a collection of datasets from our research partners (whenever appropriate), and publicly available datasets. Access to proprietary data are restricted to the users of the lab (i.e., academic staff, students, and researchers).

The lab serves as facilities for higher-level AI courses, work space for master students in AI, arena for different types of AI related arrangements such as hackathons and meetups, and serve as a demo-space for visits to NTNU from high school students etc.

We will put specific focus on building systems for sharing of code repositories, ideas and similar, in order to allow students to build on each other’s work. The lab is equipped with state-of-the art hardware and software combined with use of available cloud infrastructures, thus making the lab more agile and ready for the rapidly changing ICT landscape, enabling both lab-scale and large-scale research.