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These are some of the projects the team has been working on.
Insight Oslofjord
Insight Oslofjord is an online platform using data from student-led boat trips on the Oslofjord, organized by Inspiria Science Center. The data, collected with sensors, is processed and visualized in an R Shiny app. The platform supports both education and research by providing tools for data exploration and hypothesis testing.
Dr?bak Lander
The lander is an underwater observatory in Dr?bak sund, Oslofjord, monitoring fish and currents as part of the Frisk Oslofjord project. In collaboration with dScience, data is collected for research, with findings shared through the Insight Oslofjord app for educational use.
GeoVis
The ‘Geovis’ project, initiated by METOS researchers at the University of Oslo, aimed to develop a custom 3D visualization tool for climate datasets, improving upon the limitations of existing tools like “ncview” by enabling geographic projections and enhanced user interactions for better communication of complex climate data.
OCR-GPT pipeline
The OCR-GPT pipeline was developed to improve text data preparation for the IUROPA project by combining Adobe’s OCR for better paragraph recognition and GPT-4 for correcting character recognition errors in older EU court judgments.
Domain-adapted word embedding
Assisting a research group at the Center for Computing in Science Education in combining qualitative methods with NLP to analyse educational texts. The work includes exploring domain-adapted models and developing tools for efficient text extraction.
Neural Ratio Estimation
This project explores how neural networks can support the search for axion-like particles (ALPs) in cosmic gamma-ray data. By using Neural Ratio Estimation (NRE), researchers aim to overcome the limitations of traditional statistical methods and enable more efficient inference of ALP properties. The work is carried out by Heidi Sandaker’s group, with contributions from dSAG on high-performance computing and machine learning support.