Bio

I am a PhD student at the SAINTS Lab in the Department of Computer Science at the University of Copenhagen (UCPH). My work sits at the intersection of AI, data, and sustainability, with a focus on how machine learning systems can be designed to be socially, economically, and especially environmentally sustainable. I study data- and resource-efficient machine learning, examining how choices across the data and model lifecycle shape energy use, carbon emissions, and broader societal impact. I am supervised by Raghavendra Selvan and Erik Dam.

I hold a MSc degree in Computational Physics from the Niels Bohr Institute, UCPH, where I explored physics-informed ML as a way to reduce energy use and carbon emissions of ML models. My master’s thesis was supervised by Raghavendra Selvan and Jens Hesselbjerg Christensen.

Keywords: Sustainable, resource-efficient, frugal, and responsible machine learning and data practices.

Recent Activities and Highlights

• 2025-09: Paper on arXiv.
• 2025-09: Workshop at Det Åbne Gymnasium on “Sustainable AI” as part of the National Climate Action Day for Gymnasiums.
• 2025-08: Attended the decennial Aarhus 2025 Conference and the D3A Conference where I presented my Master’s thesis work on carbon-efficient physics-informed ML (poster, oral presentation).
• 2025-08: Started my PhD at the SAINTS Lab, Department of Computer Science, UCPH.
• 2025-05: Master’s thesis titled ‘Quantifying the Reduction in Carbon Footprint of Physics-Informed Machine Learning’ successfully defended.
• 2025-05: “Physics-Informed Machine Learning as a Carbon-Efficient Approach”. Guest presentation at PhD course on Machine Learning for Sciences, UCPH.
• 2025-05: “Hvordan er det at læse fysik på universitetet?”. Outreach talks at Falkonergårdens Gymnasium.
• 2025-04: “On the Carbon Footprint of AI: From Monitoring to Mitigation”. Joint presentation with Raghavendra Selvan at Climate Action Day, Copenhagen Center of Social Data Science, UCPH.
• 2025-03: “Quantifying the Reduction in Carbon Footprint of Physics-Informed Machine Learning”. Presentation of current thesis work at the 4th Annual Niels Bohr Institute MSc Student Symposium, UCPH.
• 2024-10: Participated in the AI Structured Learning 2024 Workshop in Göteborg.
• 2024-08: Attended the Hamlet-Physics 2024 Conference in Copenhagen.
• 2024-06: Completed an exchange semester at the Insitute of Physics, University of Amsterdam.