Quoc V. Le

Lê Viết Quốc (born 1982), or in romanized form Quoc Viet Le, is a Vietnamese-American computer scientist and a machine learning pioneer at Google Brain, which he established with others from Google. He co-invented the doc2vec and seq2seq models in natural language processing. Le also initiated and lead the AutoML initiative at Google Brain, including the proposal of neural architecture search.

Education and career
Le was born in Hương Thủy in the Thừa Thiên Huế province of Vietnam. He studied at Quốc Học Huế High School. In 2004, Le moved to Australia and attended Australian National University for Bachelor's program, during which he worked under Alex Smola on Kernel method in machine learning. In 2007, Le moved to Stanford University for graduate studies in computer science, where his PhD advisor was Andrew Ng.

In 2011, Le became a founding member of Google Brain along with his then PhD advisor Andrew Ng, Google Fellow Jeff Dean and Google researcher Greg Corrado. Le led Google Brain's first major discovery, a deep learning algorithm trained on 16,000 CPU cores, which learned to recognize cats after watching only YouTube videos, and without ever having been told what a "cat" is.

In 2014, Ilya Sutskever, Oriol Vinyals and Le proposed the seq2seq model for machine translation. In the same year, Tomáš Mikolov and Le proposed the doc2vec model for representation learning of documents. Le was among the main contributors of Google Neural Machine Translation.

In 2017, Le initiated and lead the AutoML project at Google Brain, including the proposal of neural architecture search.

In 2020, Le initiated and contributed to Meena, later renamed as LaMDA, a conversational large language model built on the seq2seq architecture. In 2022, Le and coauthors published chain-of-thought prompting, a method to improve the reasoning ability of large language models.

Honors and awards
Le was named MIT Technology Review's innovators under 35 in 2014. He has been interviewed by and his research has been reported in major media outlets including Wired, the New York Times, the Atlantic, and the MIT Technology Review. Le was named an Alumni Laureate of the Australian National University School of Computing in 2022.