About me

I am a senior research scientist at RISE Research institutes of Sweden and head of The Foundational and Applied Machine Learning for Earth Research Lab. 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 have a PhD in machine learning from Chalmers university of technology, my thesis is called Representation learning for natural language (click for details). I have worked on summarization, dialogue systems, adversarial training (for sequences, data privacy, speech), character-based RNNs, and federated learning.

I believe in the potential for AI to make the world a better place for us all, which is why much of the research projects I run are motivated by environmental or medical issues. I like listenening to the Talking Machines podcast.

I organize, and occasionally give talks in, our popular Learning Machines seminar series at RISE (and at other events). When I have time, I do enjoy writing code and perform experiments.

Richard Johansson and Devdatt Dubhashi was my PhD supervisors.

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

Teaching

I am currently supervising two PhD candidates. I frequently supervise master's students in their thesis work. See my research group page and the list of finished master student projects for more info. I have taught many courses.

Other things

When not doing research or teaching, I am a long distance runner and the lucky father of two wonderful children.

Short biography

Olof Mogren is the director of deep learning research at RISE and co-PI for CLIMES, the Swedish Center for Impacts of Climate Extremes. He obtained a PhD in machine learning from Chalmers University of Technology in 2018. He works on foundational and applied machine learning, particularly with applications in computer vision and soundscape analysis for climate change adaptation and environmental monitoring. Recent examples include applied research related to soundscape analysis and computer vision for biodiversity monitoring, efficient and distributed machine learning, remote sensing, stream flow forecasting, and smart fire detection using machine listening.

Contact

Email: first name at last name dot one.
Telephone: +46-703-969624.
ORCID: 0000-0002-9567-2218.
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