Andrew Trask

Andrew Trask is a Ph.D. student at the University of Oxford and a Research Scientist at DeepMind in London specializing in privacy and deep learning. He leads OpenMined, an open-source project dedicated to the advancement of safe, privacy-preserving deep learning. Andrew has penned the well-received book, Grokking Deep Learning, and serves as an instructor for Udacity's Deep Learning Nanodegree. He also maintains a widely-read machine learning blog.

Before pursuing his Ph.D., Andrew headed product analytics at Digital Reasoning, where he trained the world's largest neural network, a feat documented at the International Conference on Machine Learning in 2015. In 2018, Andrew launched the OpenMined project which now boasts a community of over 3,500 machine learning researchers, practitioners, and enthusiasts. His work centers on developing privacy-preserving AI systems and, at RAAIS 2019, he presented the OpenMined system that supports multi-owner AI model governance and secure training on unseen, distributed datasets.