With a background at the intersection of physics and computer science, I work to improve the accuracy of climate projections to better understand and mitigate climate change. I have worked on signal restoration in volcanic and isotopic signals in deep ice cores from Greenland to reconstruct past climates and better understand our future. My current research focuses on using artificial intelligence and deep learning to optimize climate models and enhance their predictive capabilities.
As a researcher, I place a strong emphasis on communication and teaching. I believe that our primary role as a university is to educate the researchers and citizens of the future. Therefore, I actively engage in outreach activities for the university, including Science Slam, The Green Network for Researchers, and high school visits. I also seek out teaching opportunities, particularly in programming, AI, and machine learning at my own institute.
My primary PhD project is an interdisciplinary collaboration between ENVS and the Department of Hydrology at GEUS. Additionally, I have contacts at the University of Copenhagen and DMI, with whom I consult and collaborate. Internally at the university, I leverage relationships across the faculty to support advancements in computational models and AI. At the institute level, I collaborate on both research projects (MAIA project) and development as the chair of our Sustainability Work Group.
