State-of-the-art machine-learning projects often require massive amounts of data and computational power. As a consequence, only a few groups with these resources control access to many machine-learning models. Gauri Joshi, 34, is working to change that by designing distributed computing algorithms that make it possible for such models to be trained using a network of devices such as cell phones or sensors. “It democratizes machine learning and makes it universally accessible without requiring expensive computing hardware and enormous amounts of training data,” Joshi says.