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Bilde av Skjelvareid, Martin
Bilde av Skjelvareid, Martin
Associate professor (Bodø) Department of Computer Science martin.skjelvareid@uit.no Bodø

Martin Skjelvareid

Job description

Teaching

Teaching computer science and machine learning at the department of computer science. See details under the "teaching" tab.

Research

Project leader for the "MASSIMAL" project (Mapping of Algae and Seagrass using Spectral Imaging and MAchine Learning) running from 2020-2024. The project is funded by the Research Council of Norway (8 million NOK, via "young research talents") and UiT (600,000 NOK). The goal of the project is to develop a tool for accurate mapping of marine vegetation (algae/kelp/seagrass) using hyperspectral imaging from drones.

Main research interests: Mapping of marine habitats, hyperspectral imaging with drones, and machine learning/deep learning with a focus on image segmentation. Emphasis on open research with full publication of datasets and code.

Areas of Expertise:

  • Programming (Python / Matlab)
  • Hyperspectral imaging
  • Remote sensing and Geographic Information Systems (GIS)
  • Machine learning, with a focus on image processing
  • Acoustics, with a focus on ultrasound
  • Synthetic aperture imaging (mainly with ultrasound)

Error rendering component

Research interests

Hyperspectral imaging, ultrasound, machine learning, remote sensing, drones, unmanned aerial vehicles, synthetic aperture imaging

Teaching

Taught Subjects:

DTE-2602 Introduction to Machine Learning and AI (2022 - 2024)
TEK-1504 Physics (2023-2025)
TEK-2801 Physics 2 (2022-2024)
TEK-0513 Physics (preparatory course for engineering education) (2018-2022)

Teaching Philosophy and Method:

I have extensively taught using the "flipped classroom" method, where students can watch videos introducing a topic beforehand, and classroom time is used for problem-solving, either collectively or individually. In TEK-0513 Physics, I created instructional videos for the entire curriculum, totaling 160 videos. In TEK-1504 and TEK-2801, I have been the "local teacher" in Bodø, combined with instructional videos by Per Ødegaard.

I strongly believe that teaching theoretical subjects like physics and machine learning should be linked to concrete experiences and preferably tangible objects that students can interact with in the classroom. In DTE-2602, I often organize joint walkthroughs of algorithms on the whiteboard rather than programming via a screen. In physics courses, I frequently bring physics equipment to demonstrate concepts, such as force meters, speed meters, etc.

ResearchGate
ORCID: https://orcid.org/0000-0003-2103-865X

Member of project

Massimal    English content

CV

Education:

  • Master of science (electronics) at NTNU, specializing in signal processing and acoustics
  • PhD in physics at UiT the Arctic University of Norway (subject: Synthetic aperture ultrasound imaging for water pipeline assessment)

Work experience:

  • PhD student / researcher at Breivoll Inspection Technologies, Tromsø (2008-2013)
  • Researcher at Nofima, Tromsø (2013-2018)
  • Associate professor at UiT the Arctic University of Norway (2018 ->)