Rate My Professor Fei-Fei Li

Fei-Fei Li is the inaugural Sequoia Professor in the Computer Science Department at Stanford University and Founding Co-Director of Stanford’s Human-Centered AI Institute. She earned a B.A. in physics from Princeton University in 1999 with High Honors, an M.S. in electrical engineering from the California Institute of Technology in 2001, and a Ph.D. in electrical engineering from Caltech in 2005. She has received honorary doctorates from Yale University in Engineering and Technology in 2025 and from Harvey Mudd College in Engineering in 2022. Her research specializations include artificial intelligence, deep learning, robotic learning, spatial intelligence, ambient intelligence for healthcare delivery, computer vision, and cognitive and computational neuroscience. She is renowned for inventing ImageNet and the ImageNet Challenge, foundational datasets and benchmarks that propelled the modern deep learning revolution in computer vision and AI.

Li's career includes serving as Director of Stanford’s AI Lab from 2013 to 2018, Vice President at Google and Chief Scientist of AI/ML at Google Cloud from 2017 to 2018, and currently as Co-founder and CEO of World Labs, focusing on spatial intelligence and generative AI. She holds a professorship by courtesy in Operations, Information and Technology at Stanford Graduate School of Business. Major awards encompass the Queen Elizabeth Prize for Engineering in 2025, VinFuture Prize in 2024, election to the National Academy of Engineering in 2020, National Academy of Medicine in 2020, American Academy of Arts and Sciences in 2021, ACM Fellowship in 2018, IEEE PAMI Thomas S. Huang Memorial Prize in 2022, and IEEE PAMI Longuet-Higgins Prize in 2019. She has authored over 400 publications in top venues, including "ImageNet Large Scale Visual Recognition Challenge" (2015, International Journal of Computer Vision), "Deep Visual-Semantic Alignments for Generating Image Descriptions" (2017, IEEE Transactions on Pattern Analysis and Machine Intelligence), "Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations" (2017, International Journal of Computer Vision), and the book "The Worlds I See: Curiosity, Exploration and Discovery at the Dawn of AI". Her work has had profound impact on computer science, advancing human-centered AI, and she has contributed through U.S. Congressional testimonies, UN advisory roles, and keynote lectures at NeurIPS, ICML, TED, and World Economic Forum.