About Me
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 environmentally sustainable. My research interests include 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
2026-05: “On the Challenges in Assessing the Sustainability of AI Joint”. Joint presentation with Raghav Selvan at AI and Sustainability Workshop by the Tech Policy Youth Committee, The National Center for AI in Society.
2026-05: Speaker at the P1 Workshop on Green AI.
2026-04: Paper accepted to ICML 2026! See preprint on arXiv: Stop Preaching and Start Practising Data Frugality for Responsible Development of AI.
2024-04 Invited speaker at the Embedded AI group meeting at the Technical University of Denmark.
2024-04 Invited speaker and panelist at the Sustainable AI in Practice event hosted by the Lund Stem Cell Center at Lund University.
2026-04: Paper accepted to FAccT 2026! See preprint on on arXiv: How Hyper-Datafication Impacts the Sustainability Costs in Frontier AI.
2026-03: Co-organiser and moderator of the SAINTS’26 workshop a half day workshop on Sustainable AI for Sciences.
2026-02: Guest-lecturing on AI, Resource Use, and Sustainability at Københavns Professionshøjskole.
2026-02: Participated in MLSS 2025 in Melbourne, Australia, where I presented my work on sustainability costs of hyper-datafication.
2025-12: Interviewed by Kvinder i Fysik about my transition from physics studies to research in sustainable AI.
2025-09: Preprint:Trading Carbon for Physics: On the Resource Efficiency of Machine Learning for Spatio-Temporal Forecasting 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.