Introduction
Helge Fredriksen has, throughout his career, worked at the intersection of academia and industry as a communicator, project manager, developer, and researcher.
Research
He has participated in various national and international forums with contributions in the field of deep learning and is actively working on applications within maritime, space and clinical sectors. His main research project recently has been the COFUD project, where he colaborates with Råfisklaget and The Norwegian Directory of Fisheries for research and development of improved resource control of fisheries using deep learning. The project has received funding from UiT-Talent, Råfisklaget and NScale Innovation Park.
He has supervised five master’s students in this area and has served as an academic mentor for the startup Eagle AI, who received a STUD-ENT funding (Innovation Norway, 2024) based on a multimodal deep-learning segmentation framework considering various remote sensing datasources. Read more in Dominik Thamms thesis.
He is currently an academic team member in Visual Intelligence, and is currently the main supervisor of the PhD student/Researcher Heiko Rotteveel and the master students Fredrik Eilertsen, Qandeel Maqsood, Truls Lindmark and Frode Børlie on deep learning and machine learning theses.
Teaching
In recent years, his teaching focus has shifted toward machine learning and generative AI, where he teaches various courses at the master’s program and bachelor program in Computer Science at the Bodø campus of UiT - The Arctic University of Norway. Together with Benjamin Riccaud, he is the main responsible for the master level course INF-3600 (Generative AI), while also contributing at FYS-2021 (Machine Learning) and INF-1600 (Introduction to Artificial Intelligence). He is currently also responsible for the netbased micro-course Utilizing generative AI (“Bruk av generativ KI”).
Moreover, he also is involved in the program development of the session based master programe in computer science based at the Bodø campus.