Research & Bio

My research center on the development of assistive technologies for Deaf and signing communities, including individuals with learning disabilities. More broadly, I am interested in the development of warm AI, technologies designed not only for performance but for human benefit and connection. A central focus of my work is translating advances in machine learning into practical tools that improve accessibility, inclusion, and quality of life for communities whose needs are often underserved by mainstream technological development.

Currently, I hold a position as a research assistand and PhD candidate at the Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey, supervised by Dr. Richard Bowden and Dr. Simon Hadfield. I hold a Global Talent Visa issued by UK Research and Innovation.

My strong personal connection to this area of research stems from growing up in a bilingual household, speaking both Norwegian and Norwegian Sign Language (NTS). Sign language has therefore been part of my life from early childhood, with a particular focus on signed communication used by individuals with learning disabilities. Additionally, I have also begun learning a bit of Dutch Sign Language (NGT), and am currently studying British Sign Language (BSL, Level 1).

In my current work, I research sign language processing at the intersection of computer vision, natural language processing, and sign language linguistics. While overlapping with potential benefits for d/Deaf communities, this work also holds broader potential for the wider sign language ecosystem, including individuals with neurocognitive or language-related differences who rely on visual communication to varying degrees. I am particularly interested in non-lexical sign classes, productive constructions, and the grammatical use of space, aspects of signed communication that extend beyond what can be captured in a traditional lexicon. Current work explores Sign Language Recognition and Translation, with the goal of building models capable of capturing the full expressive range of spontaneous signed communication.

Prior to my PhD, I completed an MSc in Artificial Intelligence at the University of Amsterdam (Cum Laude, ELLIS Honours). My thesis, 3D Awareness, Geometry & Linguistics in Neural Sign Language Representations, received a high distinction and was awarded the FNWI Faculty of Science Master’s Thesis Prize 2025 and the Amsterdam AI Thesis Award 2024. During the MSc I was affiliated with the SignLab Amsterdam and the AMLab, and spent a research visit at Universitat Pompeu Fabra, Barcelona.

My academic background is rooted in physics and astronomy. I completed a BSc at the University of Oslo and carried out research internships at CERN (AEgIS Group, Geneva) and Lawrence Berkeley National Laboratory (Nuclear Data Group, Berkeley). Between my BSc and MSc, I co-founded DeepSign AS, a sign language technology start-up funded by the Research Council of Norway, and BliFlink, a non-profit online tutoring platform.