Funding of project on ML-based wind farm planning obtained from the Swedish Energy Agency


We are happy to announce that we have received funding from the Swedish Energy Agency for the project AI-based Power Production Models for Increased Wind Farm Efficiency. Project summary: Wind energy is a promising source of power but is not easy to utilize effectively. Wind farms consist of many turbines that have complex interactions with each other and their surroundings. Factors such as terrain, wind trail effect (wake) between turbines, and ice accumulation on the blades influence the amount of power generated. Predicting the power output of wind farms typically relies on time-consuming simulations, but an emerging paradigm based on AI can drastically speed up prediction methods while maintaining their reliability. In this project we will develop new methods that use AI trained on real-world data to get accurate prediction of wind farm power output at a low computational cost. As the turbines and their relationships can be seen as a graph, we will use Graph Neural Networks (GNNs) to model them. Our method can have a big impact as the number of wind farms keeps growing, improving their efficiency and planning, and enabling more sustainable and affordable energy.

Aleksis Pirinen, Maria Bånkestad

Visipedia workshop @ Pioneer Centre for AI


The DL group will be represented at the Visipedia workshop hosted at the Pioneer Centre for AI in Copenhagen (to be held on April 12, 2024). The Visipedia project is jointly led by Serge Belongie’s group (University of Copenhagen) and Pietro Perona’s group (Caltech). Visipedia’s goal, broadly speaking, is to make computer vision systems that can be queried and used by large communities of experts to help foster the curation and generation of new knowledge.

Olof Mogren, Aleksis Pirinen

CLIMES kick-off meeting


CLIMES (The Swedish Centre for Impacts of Climate Extremes) is a platform for research and training to promote scientific progress in the study of climate extremes and support societal resilience. The kick-off meeting will take place on April 26th in Uppsala Sweden. Olof Mogren will give a talk on AI for tackling climate change. More info on the CLIMES web page.

Olof Mogren

DL group at ICLR 2024


The DL group will meet you at ICLR 2024! We have two papers (see here and here) to be presented at the ML4RS workshop, and Olof Mogren will be a panelist at the Tackling Climate Change with Machine Learning Workshop organized by Climate Change AI.

Olof Mogren, Aleksis Pirinen, Martin Willbo, John Martinsson, Edvin Listo Zec

Position paper about nature-based solutions presented at ECTP 2024


The NBS initiative position paper Embracing Nature-Based Solutions for Sustainable Development was presented at the ECTP conference 2024.

Aleksis Pirinen

Paper accepted for the journal Remote Sensing


The paper Creating and Leveraging a Synthetic Dataset of Cloud Optical Thickness Measures for Cloud Detection in MSI was accepted for the journal Remote Sensing (2024).

Aleksis Pirinen

Four new master theses initiated


We wecolme eight new master thesis workers to the DL group during the spring of 2024. The four associated master theses will revolve around diverse topics: ML for detecting coffee berry disease, data-efficient ML for EO, active learning for soundscape analysis, and distributed ML.

Olof Mogren, Aleksis Pirinen, Martin Willbo, John Martinsson, Edvin Listo Zec

Three Vinnova grants obtained


Three Vinnova grants obtained (Emerging Technology Solutions): Towards efficient computational fluid dynamics simulations with physics-informed machine learning, Active learning for ecological monitoring, and Structural causal models for distributional shift in federated learning.

Olof Mogren, Aleksis Pirinen, Maria Bånkestad, John Martinsson, Edvin Listo Zec

Streamflow prediction paper accepted for SAIS 2023


The paper Fully Convolutional Networks for Dense Water Flow Intensity Prediction in Swedish Catchment Areas was accepted for SAIS 2023.

Olof Mogren, Aleksis Pirinen

Paper accepted at ML-for-RS workshop at ICLR 2023


The paper Aerial View Localization with Reinforcement Learning: Towards Emulating Search-and-Rescue was accepted for the 1st ML-for-RS Workshop at ICLR 2023.

Aleksis Pirinen