About me

I am a Principal Researcher at RISE Research Institutes of Sweden, heading the RIDR group and responsible for the deep learning research area. We run a number of applied research projects where state-of-the-art techniques from machine learning transform application areas, and let new application areas drive innovation to push the boundaries of machine learning research.

I am a Docent at the Faculty of Engineering (LTH), Lund University. I hold a PhD in machine learning from Chalmers University of Technology (2018); my thesis is titled Representation learning for natural language. My PhD supervisors were Richard Johansson and Devdatt Dubhashi. My foundational work spans robust machine learning, annotation efficiency and uncertainty quantification in deep learning, and .

My applied work centers on machine learning for sustainability, specifically climate change adaptation, environmental monitoring, biodiversity tracking, remote sensing, and machine listening. I am a co-PI of CLIMES (The Swedish Centre for Impacts of Climate Extremes) and co-founder of Climate AI Nordics (CAIN), an initiative connecting Nordic researchers working on climate change challenges (visit climateainordics.com).

I organize the RISE Learning Machines seminar series. When I have time, I enjoy writing code and performing experiments.

See also my licentiate thesis, "Multi-document summarization and semantic relatedness", and master's thesis, "Dynamics of geographical routing in small-world networks".

Key research topics

• AI for climate adaptation and environmental monitoring
• Soundscape analysis and biodiversity monitoring
• Machine learning for remote sensing
• Robust machine learning
• Efficient and distributed/federated machine learning

Teaching & supervision

I am currently supervising four PhD candidates:

• John Martinsson (RISE and Lund University)
• Fan Wang (RISE and Örebro University)
• Georgios Filippis (RISE and Örebro University)
• Mateusz Wroblewski (Karolinska Institutet)

Alumni

• Edvin Listo Zec (RISE and KTH) – successfully defended PhD thesis

I frequently supervise master's students in their degree projects. See my research group page for past and open thesis topics.

I teach and give lectures in some courses, including the recurring CLIMES summer school, and the short course on AI for environmental data.

Other things

When not working, I am a long-distance runner and the lucky father of two amazing teenagers.

Short biography

Olof Mogren is a Principal Researcher heading the RIDR group at RISE, responsible for deep learning research, and Docent at the Faculty of Engineering (LTH), Lund University. Holding a PhD in machine learning from Chalmers University of Technology, his work bridges foundational machine learning and applied AI for sustainability. He is a co-founder of Climate AI Nordics and co-PI for CLIMES (Swedish Centre for Impacts of Climate Extremes). His current research topics include biodiversity and environmental monitoring, soundscape analysis, remote sensing, stream flow forecasting, robust AI, and distributed machine learning.

Contact

Email: first name at last name dot one.
Telephone: +46 10 228 43 80.
ORCID: 0000-0002-9567-2218.
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