Quoc Viet Le
Vietnamese-American computer scientist (born 1982)
Lê Viết Quốc (born 1982), or in anglicized form Quoc Viet Le, is a Vietnamese-American computer scientist and artificial intelligence researcher. He is a Google Fellow at Google DeepMind and a founding member of the Google Brain project.2
From Wikipedia’s article on Quoc Viet Le (this version), CC BY-SA 4.0.
Born 1982.1
About
Le is best known for his pioneering work in deep learning, particularly in large-scale unsupervised learning, sequence-to-sequence (seq2seq) models, and AutoML (neural architecture search). His research laid the foundation for modern machine translation systems, such as Google Translate, and advanced the field of large language models (LLMs).
From Wikipedia’s article on Quoc Viet Le, shared under CC BY-SA 4.0.2
Companies
- Discovery LoopFounder13
Early life and education
Le was born in Hương Thủy in the Thừa Thiên Huế province of Vietnam. He attended Quốc Học Huế High School before moving to Australia in 2004 to pursue a Bachelor’s degree at the Australian National University. During his undergraduate studies, he worked with Alex Smola on kernel method in machine learning. In 2007, Le moved to the United States to pursue graduate studies in computer science at Stanford University, where his PhD advisor was Andrew Ng.
In 2011, Le became a founding member of Google Brain along with his then advisor Andrew Ng, Google Fellow Jeff Dean, and researcher Greg Corrado. He led Google Brain’s first major breakthrough: a deep learning algorithm trained on 16,000 CPU cores, which learned to recognize cats by watching YouTube videos—without being explicitly taught the concept of a "cat."
In 2014, Le co-proposed two influential models in machine learning. Together with Ilya Sutskever, Oriol Vinyals, he introduced the seq2seq model for machine translation, a foundational technique in natural language processing. In the same year, in collaboration with Tomáš Mikolov, Le developed the doc2vec model for representation learning of documents. Le was also a key contributor of Google Neural Machine Translation system.
In 2017, Le initiated and led the AutoML project at Google Brain, pioneering the use of neural architecture search. This project significantly advanced automated machine learning. This work led to EfficientNet, a family of image recognition models that achieved state-of-the-art accuracy while being significantly smaller and faster than previous models.
In 2020, Le contributed to the development of Meena, later renamed LaMDA, a conversational large language model based on the seq2seq architecture. In 2022, Le and coauthors published chain-of-thought prompting, a method that enhances the reasoning capabilities of large language models.
In 2024, Le contributed to the development of AlphaGeometry, an AI system that solves complex geometry problems at a level approaching a human International Mathematical Olympiad (IMO) gold-medalist. The system, published in Nature, demonstrated the ability to solve 25 out of 30 Olympiad geometry problems, significantly outperforming previous state-of-the-art automated theorem provers.
He left Google and co-founded the AI research start-up Discovery Loop in 2026 together with Jeff Dean, Sanjay Ghemawat, and Oriol Vinyals. Their goal is to automate the entire experimental loop of science and engineering using artificial intelligence.
From Wikipedia’s article on Quoc Viet Le (this version), CC BY-SA 4.0.
Career
Occupation: researcher.6
- Since 2026Worked at Discovery Loop4
- 2013 to 2026Worked at Google4
- Date not recordedFounded Discovery Loop5
Personal life
Links
Sources
The numbers on this page point here. Each one links to the record it came from.
- 1WikidataQuoc Viet Le on Wikidata
- 2WikipediaQuoc Viet Le on Wikipedia
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- 8Wikidataplace of birth, as reported
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- 11WikidataQuoc Viet Le: X, on Wikidata
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- 13WikidataDiscovery Loop, Founder