About

Short version: Senior ML researcher at RISE – Co-founder of Climate AI Nordics – Core team member of the GEO AI4EO working group – Affiliated with CLIMES – Part of the Computing within Limits community

Long version: I’m a senior machine learning researcher at RISE Research Institutes of Sweden within the deep learning research group, where my main research interest is to develop ML methods for a broad range of environmental applications (e.g. climate adaptation and humanitarian aid causes). I’m a co-founder of the research network Climate AI Nordics, am affiliated with the Swedish Centre for Impacts of Climate Extremes (climes), and am a core team member of the GEO AI4EO working group.

Before joining RISE, I conducted my doctoral studies in computer vision at the Faculty of Engineering, Lund University, under the supervision of Prof. Cristian Sminchisescu. In my research, I applied deep reinforcement learning to computer vision tasks such as object detection and active vision, with the aim of making visual recognition systems more flexible and adaptive. I successfully defended my PhD thesis Reinforcement Learning for Active Visual Perception in June, 2021.

I’m an advocate for facing our difficult future (and present, for many), collectively and individually, so that we can try to reduce harm and suffering. I may write more about this under my personal page at some point, but for anyone interested in learning more about what is difficult about our future, I warmly recommend the podcasts The Great Simplification, Breaking Down: Collapse (and the follow-up podcast Building Up: Resilience), Planet: Critical, and Entangled World. Two other short and self-contained podcasts that I also recommend are Power: Limits and Prospects for Human Survival and Tipping Point: The True Story of “The Limits to Growth”. I also try to summarize some reasons why in this video.

News

Oct 2025: New preprint summarizing our work on SatML for grazing detection, jointly with the Swedish Board of Agriculture! Grazing plays a key roll for maintaining important biodiversity hotspots, e.g. semi-natural pastures – and in this work, we scale up grazing monitoring efforts with SatML! Code and models are available.

Sep 2025: Thrilled to be in the organizing committee of the EurIPS 2025 accepted workshop AICC: Workshop on AI for Climate and Conservation (Call for Participation deadline Oct 10).

April 2025: Funding obtained for the upcoming 4-year doctoral project ML-Earth: Robust and data-efficient machine learning for Earth observation from the Swedish Foundation for Strategic Research. I will be PI and main supervisor in this project (starting Dec 2025), and co-supervisor will be Prof. Yifang Ban.

March 2025: Invited presentation about Climate AI Nordics to the Young European Associated Researchers network (YEAR).

Feb 2025: Funding obtained from the Swedish National Space Agency for the project AI-based remote sensing for monitoring nature restoration and landscape elements at farm level. I will be PI in this 2-year project, which starts in April 2025.

Dec 2024: We’re organizing the 2025 Nordic Workshop on AI for Climate Change in May 2025, the first of a hopefully annual series of workshops/conferences hosted by Climate AI Nordics!

Dec 2024: I’ve joined the core team of the GEO AI4EO working group, led by Prof. Yifang Ban.

Oct 2024: Excited and proud to have founded the new Nordic research network Climate AI Nordics, together with my amazing colleague Olof Mogren! Welcome to join the network!

Sept 2024: Paper accepted at NeurIPS 2024! Check out our work on aerial exploration across modalities, relevant e.g. for search-and-rescue operations. Code is available!

Aug 2024: As of this month, I’m affiliated also with the Swedish Centre for Impacts of Climate Extremes (CLIMES) funded by the Swedish Research Council.

Sept 2023: I was the main organizer of the hackathon Walking on Thin Clouds in Stockholm, where participants explored our recently developed ML methods for cloud optical thickness estimation in Sentinel-2 imagery. It was a really fun day!

Oct 2022: My work on AI-based mapping of Swedish wetlands, for the Swedish Environmental Protection Agency, got covered in the Swedish magazine Miljö & utveckling.

Sept 2021: I started working as an ML researcher at RISE Research Institutes of Sweden, in Lund. I’m part of RISE’s deep learning research group (RIDR).

June 2021: On June 10th, I successfully defended my doctoral thesis Reinforcement Learning for Active Visual Perception (a video overview can be seen here). Looking forward to a summer break before starting as an ML researcher at RISE in September!

Publications and preprints

Please refer to this page, and/or my google scholar page.

Selection of past and ongoing projects

Please refer to this page for a selection of my past and ongoing projects.

Past and ongoing doctoral supervision

Below is a description of past and ongoing doctoral student supervision. Please see this page for past and ongoing master thesis and internship supervision.

Dec 2025 - Dec 2029 (upcoming): Main supervisor for PhD candidate Isabelle Tingzon, who will also be affiliated with KTH Royal Institute of Technology. Academic supervisor: Prof. Yifang Ban (KTH). The doctoral project is titled ML-Earth: Robust and data-efficient machine learning for Earth observation and is funded by the Swedish Foundation for Strategic Research.

May 2023 - Feb 2025: Co-supervisor for PhD candidate Maria Bånkestad (RISE, Uppsala University). Academic supervisor: Prof. Thomas Schön (Uppsala University). Maria successfully defended her thesis in Feb 2025: Structured models for scientific machine learning: from graphs to kernels.

Media and public communication

Please refer to this page for a selection of invited talks as well as media and public communication.

Honors, awards and review work

Please refer to this page.