Publications: 'Multi-Class Segmentation from Aerial Views using Recursive Noise Diffusion', WACV 2024; 'DDOS: The Drone Depth and Obstacle Segmentation Dataset', CVPR 2024; 'UCorr: Wire Detection and Depth Estimation for Autonomous Drones', ROBOVIS 2024.
Research Experience
Co-founder & CTO at Regava, June 2024 - Present, Leading research and development of LLM-powered solutions for regulatory compliance in financial services. Research Scientist at Deepair, May 2018 - June 2022 (Part-time), Developed and deployed reinforcement learning systems for automated pricing in the travel industry. Data Scientist at Icelandic COVID-19 Vaccine Taskforce, April 2021 - June 2021, Led data science initiatives that increased daily vaccination rates from 5k to 17k, implemented live monitoring systems, and optimized patient recruitment through predictive analytics during Iceland's national vaccination programme.
Education
PhD: Imperial College London, 2025, Research in AI and machine learning, focusing on computer vision and autonomous systems. MEng: Imperial College London, 2019, Electrical and Electronic Engineering with Management, Thesis on GANs for domain transfer. High School: Verzlunarskóli Íslands, 2015, Physics track with foundation studies in mathematics and sciences.
Background
Research Interests: Advancing deep learning methods and developing novel approaches to solve challenging problems, specializing in computer vision, particularly for fully autonomous drones, LLMs, RAG, diffusion models, and knowledge distillation. Professional field: Artificial Intelligence, focusing on practical applications that can solve real-world challenges.
Miscellany
Current Focus: Balancing entrepreneurial ventures with cutting-edge research, working to translate advanced AI research into practical solutions that can benefit society and industry.