Dr. Fei-Fei Li
Sequoia Professor of Computer Science; Co-Director, Stanford HAI
Co-author of framework underlying SB-53; AI working group member
Dr. Fei-Fei Li is the Sequoia Professor of Computer Science at Stanford University and Co-Director of the Stanford Institute for Human-Centered Artificial Intelligence (Stanford HAI). Often called the “godmother of AI,” she is one of the most influential figures in the history of modern artificial intelligence — best known for creating ImageNet, the large-scale visual database whose 2012 competition results triggered the deep learning revolution that underlies virtually all contemporary AI systems.
Born in Beijing and raised in Chengdu, China, Li immigrated to the United States at age 16. She earned her bachelor’s degree in physics from Princeton University and her PhD in electrical engineering from the California Institute of Technology, where she studied under Pietro Perona and Christof Koch. She served as Director of the Stanford Artificial Intelligence Laboratory from 2013 to 2018 and as Chief Scientist of AI/ML at Google Cloud from 2017 to 2018. In 2017, she co-founded AI4ALL, a nonprofit dedicated to increasing diversity and inclusion in artificial intelligence education.
Li’s research spans computer vision, machine learning, deep learning, and cognitive neuroscience. She has been elected to the National Academy of Engineering, the National Academy of Medicine, and the American Academy of Arts and Sciences, and was named to the Time 100 AI Most Influential People list in 2023. She received the Queen Elizabeth Prize for Engineering in 2025.
Following Governor Newsom’s veto of SB-1047 in September 2024, Li joined Justice Mariano-Florentino Cuéllar and Dean Jennifer Tour Chayes as a co-author of the landmark California AI working group report published in March 2025 — a first-of-its-kind, science-based analysis of frontier AI capabilities and governance frameworks. That report directly shaped SB-53. Although Li had opposed SB-1047 on the grounds that it was overly broad and could harm open-source AI development, she engaged constructively in the evidence-based process that produced SB-53’s more targeted approach.
At the signing of SB-53 on September 29, 2025, Li co-signed a joint statement affirming that the law’s transparency and “trust but verify” principles aligned with the working group’s recommendations. Her doctoral students include Andrej Karpathy, Olga Russakovsky, and Timnit Gebru — among the most prominent figures in contemporary AI research.