Fei-Fei Li

Why Fei-Fei is the canonical Working Researcher

Fei-Fei Li built the empirical foundation on which modern AI vision rests. Born in Beijing in 1976 and raised in Chengdu, she immigrated to the United States at sixteen, earned a BA in physics from Princeton in 1999 while working at the family dry-cleaning business, then completed her PhD in electrical engineering at Caltech in 2005. After faculty positions at Illinois and Princeton, she joined Stanford in 2009, was tenured in 2012, and became a full professor in 2018. Between 2013 and 2018 she directed the Stanford Artificial Intelligence Laboratory, and later co-founded and co-directs Stanford's Human-Centered AI Institute alongside former provost John Etchemendy. Her publication record exceeds 300 peer-reviewed papers spanning computer vision, deep learning, machine learning, cognitive neuroscience, and computational neuroscience.

The single work that defines Li's career is ImageNet, which she initiated while at Princeton in 2007. The project assembled more than 14 million annotated images using Amazon Mechanical Turk to create the largest visual database of its kind, then launched the ImageNet Large Scale Visual Recognition Challenge — a benchmark competition that drove the dramatic error-rate collapse in image classification between 2010 and 2017, including AlexNet's breakthrough result in 2012. This is the Working Researcher role distilled to its purest form: a salaried university scientist who identified a structural gap in the field — the absence of large, clean, annotated training data — framed it as a tractable institutional problem, secured the resources to solve it, and produced a peer-reviewed artifact that reshaped every downstream application from autonomous vehicles to medical imaging. The contribution was neither a solitary invention nor a commercial bet; it was organized academic science executing at frontier scale.

Li took a sabbatical at Google Cloud as Chief Scientist of AI/ML and Vice President from early 2017 to late 2018, returning to Stanford thereafter. In 2017 she co-founded AI4ALL, a nonprofit with Melinda French Gates and Jensen Huang to broaden diversity in AI education. In 2023 she was named to Time's AI 100 and appointed to the United Nations Scientific Advisory Board. She was elected to the National Academy of Engineering and National Academy of Medicine in 2020, the American Academy of Arts and Sciences in 2021, and received the Queen Elizabeth Prize for Engineering in 2025. In 2024, on partial leave from Stanford, she co-founded World Labs, a startup focused on spatial intelligence — reasoning about three-dimensional physical environments — which raised $230 million in its first year and over $1 billion by 2026.

The Working Researcher salaried researcher inside an organized research function — publishes, wins grants, builds citation impact. See the Working Researcher role →

Same role, different wave