Ketil Malde

Ketil Malde is an Associate Professor at the Department of Informatics, University of Bergen. He is affiliated with the Norwegian Marine Data Center and the Institute of Marine Research. His research focuses on applying machine learning and bioinformatics to marine science challenges, including genome sequencing, acoustic data analysis, and fisheries management.

Education: PhD in Algorithms for the Analysis of Expressed Sequence Tags (2005, University of Bergen).

Research Interests: Bioinformatics, marine genomics, deep learning applications in fisheries science, acoustic signal processing, and automated data analysis for marine ecosystems.

Scientific Contributions: Developed tools like DeepOtolith for fish age estimation, contributed to the salmon louse genome project, and pioneered methods for acoustic target classification using deep learning. His work bridges computational methods with ecological and fisheries management needs.

Projects: CRIMAC (Center for Research-based Innovation in marine acoustic abundance estimation), COGMAR, and collaborations with Scantrol Deep Vision for eco-friendly fish sampling.

Supervised students include Peter Løkhammer Liessem (object tracking for catch estimation) and Knut T. A. Holager (acoustic frequency subset selection). Active in organizing workshops like the Norway-U.S. Machine Learning in Marine Science collaboration.