He published Apple's first research paper on AI, which then won the Best Paper Award at the Conference on Computer Vision and Pattern Recognition. His work has contributed to the development of autonomous vehicles, Face ID in the iPhone X, facial microexpression detection, and sign language translation – it also landed him on Forbes' 30 Under 30 in Science for 2018. With a vision that artificial intelligence can improve lives, Tomas Pfister has poured himself into AI research, hoping to have a positive impact on the world with this powerful technology. In this exclusive interview, Pfister discusses the origins of his scientific interest, what made his Apple paper so innovative, and his current research with Google. Tomas Pfister: As a child I was always fascinated by computers.

Apple's first public research paper on AI was penned by vision expert Ashish Shrivastava and a team of engineers including Tomas Pfister, Oncel Tuzel, Wenda Wang, Russ Webb and Apple Director of Artificial Intelligence Research Josh Susskind, appleinsider.com Shrivastava holds a PhD in computer vision from the University of Maryland. Titled'Learning from Simulated and Unsupervised Images through Adversarial Training', the paper describes techniques of training computer vision algorithms to recognise objects using synthetic, or computer generated, images. However, learning from synthetic images may not achieve the desired performance owing to a gap between synthetic and real image distributions. To reduce this gap, Apple has proposed Simulated plus Unsupervised (S U) learning, where the task is to learn a model to improve the realism of a simulator's output using unlabelled real data while preserving the annotation information from the simulator.