Blur Labs models have applications from medical imaging to earth observation. Blur Labs created an open-source proof of concept called the Reconstruct Anything Model that is trained to solve a wide range of imaging inverse problems, such as deblurring, magnetic resonance imaging (MRI) and computed tomography (CT). Blur Labs’ mission is to harness AI to power the imaging devices of the future by removing the cost of image acquisition. In cancer imaging, Blur Labs aims to reduce waiting times for diagnosis and therapy by increasing the rate at which patients are scanned. In routine imaging, Blur Labs aims to expand access to medical imaging by powering cheaper, portable hardware. In remote sensing, Blur Labs aims to push the boundaries of Earth observation from space by increasing image quality for a given satellite. Andrew, co-founder and Chief Technology Officer of Blur Labs, currently studies AI approaches to imaging inverse problems at the School of Engineering. While working on an open-source software project, DeepInverse, a deep learning library for image reconstruction, Andrew met two of its maintainers and co-creators, Julián Tachella and Matthieu Terris, and together launched Blur Labs. Andrew Wang commented, I started contributing to open-source when I started my PhD as it let me meet, collaborate with and learn from a more diverse range of researchers and practitioners beyond Edinburgh and my immediate research field. I was fortunate to have the University of Edinburgh and my supervisor, Professor Mike Davies, allow me to develop these networks and ultimately found a startup with international collaborators. Blur Labs is now growing, with customers from Europe to the US to Asia.Related links Blur Labs | AI foundation models for imaging DeepInverse: a Python library for imaging with deep learning Reconstruct Anything Model: a lightweight general model for computational imaging Publication date 29 Oct, 2026
