about the authors

Howard Huang is a software engineer who has worked on the PyTorch library for over five years and been an avid user for even longer. He has a background in distributed systems and ML systems, working on distributed training for most of his career. At publication, he is on the PyTorch team at Meta.

Luca Antiga worked as a researcher in biomedical engineering in the 2000s and spent the last decade as a cofounder and CTO of an AI engineering company. He has contributed to several open source projects, including the PyTorch core. He recently cofounded a US-based startup focused on infrastructure for data-defined software.

Eli Stevens has spent most of his career working at startups in Silicon Valley, with roles ranging from software engineer (making enterprise networking appliances) to CTO (developing software for radiation oncology). At publication, he is working on machine learning in the self-driving-car industry.

Thomas Viehmann is a machine learning and PyTorch specialty trainer; a consultant based in Munich, Germany; and a PyTorch core developer. With a PhD in mathematics, he is not scared by theory, but he is thoroughly practical when applying it to computing challenges.