Fei-Fei Li

Fei-Fei Li

Computer Scientist, Professor, Entrepreneur

Fei-Fei Li, computer scientist and AI researcher

Personal Details
Born	1976 Beijing, China
Nationality	Chinese-American
Career & Education
Occupation	Computer Scientist, Professor, Entrepreneur
Education	Physics; Electrical Engineering
Alma Mater	Princeton University; California Institute of Technology
Institution	Stanford University; World Labs
Known For	ImageNet, computer vision, human-centered artificial intelligence and spatial intelligence
Years Active	2005–present
Recognition & Links
Awards	Queen Elizabeth Prize for Engineering; VinFuture Prize; Intel Lifetime Achievement Award; IEEE PAMI Longuet-Higgins Prize
Website	Official Website

Fei-Fei Li is a Chinese-American computer scientist, artificial intelligence researcher, professor and entrepreneur. She is the Sequoia Professor of Computer Science at Stanford University and a founding leader of Stanford's Institute for Human-Centered Artificial Intelligence. She is also the co-founder and CEO of World Labs, an artificial intelligence company focused on spatial intelligence and generative AI. ([stanford.edu](https://profiles.stanford.edu/fei-fei-li))

Li is particularly known for her work in computer vision, machine learning and deep learning. She is the creator of ImageNet, a large-scale image dataset and benchmark that became an important resource in the development of modern computer vision and deep-learning systems.

Her career combines academic research, artificial intelligence development, technology entrepreneurship and work on the social implications of AI. She has also advocated for broader participation in artificial intelligence education through the nonprofit AI4ALL.

Early life and education

Fei-Fei Li was born in Beijing, China, in 1976. She later moved to the United States and pursued higher education there.

She attended Princeton University, where she earned a Bachelor of Arts degree in Physics in 1999 with high honors. She subsequently studied electrical engineering at the California Institute of Technology (Caltech), receiving a master's degree in 2001 and a PhD in 2005. ([stanford.edu](https://profiles.stanford.edu/fei-fei-li))

Her academic training combined physics, mathematics, engineering and computational methods. These disciplines later contributed to her research into how machines can interpret visual information.

Academic career

After completing her doctorate, Li began her academic career as a faculty member at the University of Illinois Urbana-Champaign. She subsequently joined Princeton University before moving to Stanford University in 2009.

At Stanford, she became a professor of computer science and developed a research program focused on computer vision and machine learning.

Li served as Director of the Stanford Artificial Intelligence Laboratory from 2013 to 2018. She later became a founding co-director of Stanford's Institute for Human-Centered Artificial Intelligence, an interdisciplinary institute focused on the development and use of AI in ways that consider human needs and societal effects. ([hai.stanford.edu](https://hai.stanford.edu/people/fei-fei-li))

In 2026, Stanford reorganized its AI and data-science efforts. Li took on a university-wide role as a special advisor on AI and became co-chair of the institute's advisory council. ([hai.stanford.edu](https://hai.stanford.edu/news/stanford-merges-ai-and-data-science-efforts-under-single-institute))

ImageNet

One of Li's most significant contributions to artificial intelligence is ImageNet, a large-scale database of labeled images designed to support research in visual recognition.

Li and her research collaborators began developing ImageNet in the mid-2000s. The project sought to provide researchers with a much larger and more diverse collection of images than was commonly available for computer-vision experiments.

The ImageNet project eventually contained millions of images organized according to a large hierarchical classification system. It also produced the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), an annual computer-vision competition.

The dataset and competition became important benchmarks for evaluating image-classification algorithms. Stanford describes ImageNet and the ImageNet Challenge as major contributions to the development of modern deep learning and computer vision. ([stanford.edu](https://profiles.stanford.edu/fei-fei-li))

Influence on deep learning

ImageNet became particularly important when researchers began using large neural networks and graphics processors to train image-recognition systems.

The 2012 ImageNet competition was a major milestone in the adoption of deep neural networks for computer vision. The success of AlexNet, developed by Alex Krizhevsky, Ilya Sutskever and Geoffrey Hinton, demonstrated the effectiveness of deep convolutional neural networks on large-scale image-recognition tasks.

Li's ImageNet project provided the large dataset and benchmark used to evaluate competing computer-vision systems.

This development contributed to a broader shift in artificial intelligence research toward large datasets, deep neural networks and high-performance computing.

Computer vision research

Li's research has extended beyond image classification into broader areas of visual intelligence.

Her academic work has addressed object recognition, scene understanding, visual representation, human activity recognition and the relationship between visual perception and cognition.

She has also investigated connections between artificial vision and biological vision, including research involving computational neuroscience.

Her current research interests include deep learning, robotic learning, spatial intelligence, cognitively inspired AI and AI applications in healthcare. ([stanford.edu](https://profiles.stanford.edu/fei-fei-li))

Google career

Between 2017 and 2018, Li took a leave of absence from Stanford and joined Google.

She served as a Vice President at Google and Chief Scientist of AI and Machine Learning at Google Cloud. During this period, she worked on the development and application of machine-learning technologies within Google's cloud business. ([stanford.edu](https://profiles.stanford.edu/fei-fei-li))

Her industry experience gave her an opportunity to work on large-scale AI systems beyond academic research and contributed to her later interest in connecting research, technology development and public policy.

Human-centered artificial intelligence

Li has become an advocate for a human-centered approach to artificial intelligence.

Her work at Stanford HAI has focused on bringing together computer science, medicine, law, education, social science and other disciplines to study the development and impact of AI.

Her research interests include AI and healthcare, particularly ambient intelligent systems that could assist healthcare professionals and patients.

Li has also participated in discussions concerning AI policy, responsible technology development and the role of human values in technological systems.

AI4ALL

In 2015, Li co-founded AI4ALL, a nonprofit organization focused on increasing diversity and inclusion in artificial intelligence education.

AI4ALL develops educational programs intended to introduce students from underrepresented groups to AI and related fields.

The organization reflects Li's broader interest in expanding access to AI education and increasing participation from people with different backgrounds and experiences. ([stanford.edu](https://hai.stanford.edu/people/fei-fei-li))

World Labs

Li entered the startup sector as a co-founder of World Labs, an AI company focused on spatial intelligence.

World Labs develops artificial-intelligence systems designed to understand and reason about three-dimensional environments and the physical world.

Li serves as the company's Chief Executive Officer while continuing her academic work at Stanford. Stanford's current profile identifies her as co-founder and CEO of World Labs and describes the company as focusing on spatial intelligence and generative AI. ([stanford.edu](https://profiles.stanford.edu/fei-fei-li))

The company's work reflects Li's broader research interest in moving AI systems beyond two-dimensional image recognition toward richer representations of physical environments.

AI and healthcare

Healthcare is another important area of Li's research.

At Stanford, she has worked on artificial intelligence systems that can interpret visual and other forms of information in medical environments. Her research interests include ambient intelligence, where computing systems can operate unobtrusively within healthcare settings.

Her work has involved collaborations between computer scientists, physicians, engineers and researchers from other disciplines.

The goal of this research includes developing AI systems that can support healthcare delivery while keeping human professionals involved in decision-making. ([stanford.edu](https://med.stanford.edu/raisehealth/leadership/fei-fei_li.html))

Policy and public service

Li has participated in discussions about artificial intelligence policy in the United States and internationally.

She has testified before the U.S. Congress and worked with policymakers on issues involving AI research, education and responsible technological development.

She served as a member of the National Artificial Intelligence Research Resource Task Force, organized by the National Science Foundation and the White House Office of Science and Technology Policy.

She has also served as a special advisor to the Secretary-General of the United Nations. ([stanford.edu](https://profiles.stanford.edu/fei-fei-li))

Her policy work has focused on encouraging research and technological development while considering social, economic and human consequences.

Books and public communication

Li is the author of the memoir The Worlds I See: Curiosity, Exploration and Discovery at the Dawn of AI, published in 2023.

The book combines her personal experiences with an account of the development of artificial intelligence and computer vision.

She has also delivered keynote speeches at major technology and academic conferences, including NeurIPS, ICML, the World Economic Forum and TED. ([stanford.edu](https://profiles.stanford.edu/fei-fei-li))

Awards and recognition

Li has received numerous awards for her contributions to artificial intelligence, computer vision and engineering.

She received the Queen Elizabeth Prize for Engineering in 2025 and the VinFuture Prize in 2024. She also received the Intel Lifetime Achievement Award in 2023 and the IEEE PAMI Thomas Huang Memorial Prize in 2022. ([stanford.edu](https://profiles.stanford.edu/fei-fei-li))

Earlier honors include the IEEE PAMI Longuet-Higgins Prize, the IAPR J.K. Aggarwal Prize, the IEEE PAMI Mark Everingham Award, the Alfred P. Sloan Research Fellowship and the NSF CAREER Award.

Li has been elected to the National Academy of Engineering, the National Academy of Medicine and the American Academy of Arts and Sciences. She is also a Fellow of the Association for Computing Machinery.

In 2025, TIME named Li its Person of the Year as part of its recognition of the people and developments it considered most influential during the year. ([stanford.edu](https://profiles.stanford.edu/fei-fei-li))

Personal and professional profile

Li's career spans academia, industry, entrepreneurship and public policy.

Her work on ImageNet established a major foundation for large-scale computer-vision research, while her later work has focused increasingly on human-centered AI, robotics, healthcare and spatial intelligence.

She has also become a prominent public communicator on artificial intelligence, frequently discussing both the technical development of AI and questions concerning its impact on society.

Legacy

Fei-Fei Li is associated with several important stages in the development of modern artificial intelligence.

Her creation of ImageNet helped provide the data and evaluation infrastructure that enabled researchers to compare large-scale computer-vision systems. The project's importance became especially visible during the deep-learning expansion of the early 2010s.

Her subsequent academic and industry work has expanded into human-centered AI, healthcare, robotics and spatial intelligence.

Through Stanford, AI4ALL and World Labs, Li continues to work across research, education, entrepreneurship and AI development. Her career illustrates the progression of computer vision from academic research into a major component of contemporary artificial intelligence.

See also

• Artificial intelligence
• Machine learning
• Deep learning
• Computer vision
• ImageNet
• Stanford University
• Stanford Institute for Human-Centered Artificial Intelligence
• World Labs
• AI4ALL
• Google
• Robotics

External links

• Fei-Fei Li – Stanford University
• Fei-Fei Li – Stanford HAI
• World Labs
• AI4ALL