James Thornton

James Thornton is a skilled Machine Learning Engineer with expertise in neural networks, focused on AI for factories to detect hardware defects. His work is at the intersection of machine learning and software engineering. Alongside his professional role at Instrumental, James dedicates his spare time to studying quantum physics, mathematics, prototyping deep learning research ideas, and creating AI artwork using GAN latent spaces. With a track record of winning national and international machine learning competitions, he has significantly enhanced deep learning models for cell detection and prototyped cutting-edge solutions at Berkeley Lights. James contributed to machine learning consulting projects for Tesco, the third largest retailer globally, with the Oxford Strategy Group. In his previous roles, he tackled software engineering challenges at Genospace, enabling personalized cancer treatments based on genomic profiles.