Fartash Faghri is a machine learning researcher at Apple Machine Learning Research (MLR). His research centers on enhancing the efficiency of foundation model training. Specifically, he has contributed to improving quality and effectiveness of training datasets, developing techniques for training on-device foundation models, and designing benchmarks and novel strategies for large-scale continual learning. Fartash joined Apple in 2021 following the completion of his PhD at the University of Toronto. His doctoral research delved into the development of fast and robust training methods.