Dr. Fei-Fei Li
Dr. Fei-Fei Li immigrated from China at 16, worked in her family's dry-cleaning shop and as a dishwasher, and went on to earn a physics degree from Princeton and a PhD from Caltech. She created ImageNet — the 14-million-image dataset that made modern AI possible — co-directed Stanford's Human-Centered AI Institute, and now leads World Labs, a spatial intelligence company. Her memoir The Worlds I See was selected by Barack Obama as essential reading on AI. She is a member of all three U.S. National Academies and was named one of TIME's Architects of AI (2025).
profiles.stanford.edu/fei-fei-liDr. Fei-Fei Li on human-centered AI, ImageNet, and the future of intelligence
Fei-Fei Li's most valuable talks bridge the technical and the human — explaining how AI works, why it matters, and who gets to build it. These videos collect her TED talks, major interviews, and keynotes on spatial intelligence and human-centered AI.
Interviews and the human side of AI
These longer conversations go deeper into her personal story — the immigrant journey, the responsibility of building AI, and what it means to be 'the godmother of AI.'
I believe in human-centered AI to benefit people in positive and benevolent ways.
The Dishwasher Who Made Modern AI Possible
Fei-Fei Li was born in Beijing, China on July 3, 1976, and raised in Chengdu in Sichuan Province. At 16, she immigrated to the United States with her parents, settling in Parsippany, New Jersey. The family was poor. Her father worked in a camera shop. Her mother’s health was fragile. Fei-Fei worked weekends at their dry-cleaning shop and took a job as a dishwasher to help support the household while absorbing a new language and a new school system. She earned a scholarship to Princeton University, where she graduated with High Honors in Physics in 1999, supported by the Paul & Daisy Soros Fellowship for New Americans. She completed her PhD in Electrical Engineering at Caltech in 2005, where her research bridged computational models of visual recognition with human psychophysics.
In 2007, while an assistant professor at Princeton, she began building ImageNet — a database of over 14 million labeled images across 22,000 categories. It was an audacious project at a time when most AI researchers were focused on algorithms, not data. The annual ImageNet Large Scale Visual Recognition Challenge (2010–2017) drove dramatic breakthroughs in computer vision and is now regarded as one of the three driving forces behind the modern AI revolution. She joined Stanford in 2009, earned tenure in 2012, directed the Stanford AI Lab from 2013 to 2018, and became the founding co-director of the Stanford Institute for Human-Centered AI (HAI). She also served as Chief Scientist of AI/ML at Google Cloud, where she led efforts to democratize AI through tools like AutoML, and co-founded AI4ALL with Melinda French Gates and Jensen Huang to diversify the pipeline of AI researchers.
Today, Dr. Li is the Sequoia Professor of Computer Science at Stanford and CEO of World Labs, a spatial intelligence company that raised $1 billion at a $5 billion valuation to build AI that perceives and interacts with the 3D world. She is one of an extraordinarily small number of people elected to all three U.S. National Academies (Engineering, Medicine, and Arts & Sciences). Her 2023 memoir The Worlds I See was selected by Barack Obama as essential reading on AI. In 2025, she was featured on the cover of TIME Magazine as one of the eight “Architects of AI.” Her h-index of 176 and 348,000+ citations make her one of the most cited computer scientists on the planet. The dishwasher from Chengdu became one of the most important scientific voices of her generation — and she has never stopped arguing that the technology should serve people, not the other way around.
Where to Go From Here
Pair Fei-Fei Li with Elon Musk for the contrasting visions of AI development (human-centered vs. accelerationist), and David Ondrej AI for the practical AI-builder perspective. For another pioneering woman in tech leadership, see Michelle Obama. Browse the full AI & Technology library.
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Key Ideas from Dr. Fei-Fei Li
AI must be human-centered
Fei-Fei Li's core argument: artificial intelligence should be designed to enhance human dignity, not replace human judgment. Technology serves people, not the other way around.
Who builds AI matters
She co-founded AI4ALL to diversify the pipeline of AI researchers. The people building the technology determine what problems it solves and for whom.
Curiosity as a career strategy
Her path from dishwasher to Stanford professor was powered by relentless curiosity — asking bigger questions each time she answered the last one.
Books by Dr. Fei-Fei Li
The Worlds I See
A 'science memoir' intertwining her immigrant journey with the birth of modern AI. Barack Obama recommended it as essential reading on AI. Financial Times Best Book of 2023.
Computer Vision: From 3D Reconstruction to Visual Recognition
The foundational computer vision textbook for advanced students and researchers.
Dr. Fei-Fei Li resources
Start with her memoir and her TED talks, then explore Stanford HAI and World Labs.
Dr. Fei-Fei Li FAQ
Quick answers for readers discovering Dr. Fei-Fei Li through Self Growth Videos.
What is Dr. Fei-Fei Li best known for?
She is best known as the creator of ImageNet — the dataset of over 14 million labeled images that is widely credited with sparking the modern deep learning revolution. She is also the founding co-director of Stanford's Institute for Human-Centered AI (HAI) and a leading voice for ethical, human-centered artificial intelligence.
What is her personal story?
She immigrated from China at age 16, worked in her family's dry-cleaning shop and as a dishwasher while attending high school in New Jersey, and went on to earn a physics degree from Princeton and a PhD from Caltech. Her memoir The Worlds I See weaves this immigrant story together with the birth of modern AI.
Why is she called 'the godmother of AI'?
While others are called 'godfathers of AI' for theoretical contributions, Fei-Fei Li earned the 'godmother' title for building the practical foundation — ImageNet — that made modern computer vision and deep learning possible, while simultaneously advocating that AI serve human needs.
