Fei-Fei Li 

Fei-Fei Li, born in 1976 in Beijing, China, is a prominent Chinese-American computer scientist renowned for her significant contributions to artificial intelligence (AI), particularly in computer vision and machine learning. Her pioneering work has been instrumental in advancing AI technologies and promoting a human-centered approach to AI development.

Early life and education

Li spent her early years in Chengdu, China, before immigrating to the United States at the age of 15. Adjusting to a new culture and language, she demonstrated exceptional academic abilities, leading her to pursue higher education in the sciences. She earned a Bachelor of Arts in Physics with High Honors from Princeton University in 1999. Following her undergraduate studies, Li obtained her Ph.D. in Electrical Engineering from the California Institute of Technology (Caltech) in 2005.

Academic and professional career

After completing her doctorate, Li embarked on an academic career that included positions as an assistant professor at the University of Illinois Urbana-Champaign and Princeton University. In 2009, she joined Stanford University, where she became an associate professor and later served as the Director of the Stanford Artificial Intelligence Laboratory (SAIL) from 2013 to 2018. During her tenure at Stanford, Li co-founded the Human-Centered AI Institute, emphasizing the importance of aligning AI development with human values and societal needs.

In 2017, Li took a sabbatical from Stanford to join Google Cloud as Vice President and Chief Scientist of AI/ML, where she focused on democratizing AI technology and developing tools like AutoML to make machine learning more accessible. After her tenure at Google, she returned to Stanford and continued her research and advocacy for ethical AI practices.

Contributions to AI and computer vision

One of Li’s most notable contributions is the creation of ImageNet, a large-scale dataset designed to advance object recognition research. Launched in 2009, ImageNet provided millions of labeled images across thousands of categories, serving as a critical resource for training and evaluating machine learning models. The annual ImageNet Large Scale Visual Recognition Challenge became a benchmark for assessing advancements in computer vision and deep learning.

Li’s research interests encompass AI, machine learning, deep learning, computer vision, robotic learning, and ambient intelligence for healthcare delivery. She has published over 400 scientific articles in top-tier journals and conferences, contributing significantly to the advancement of AI technologies.

Awards and honors

Throughout her career, Li has received numerous accolades recognizing her contributions to science and technology. These include the Microsoft Research New Faculty Fellowship (2006), the NSF CAREER Award (2009), and being named a Fellow of the Association for Computing Machinery (ACM) in 2018 for her work in building large knowledge bases for machine learning and visual understanding. In 2020, she was elected as a member of both the National Academy of Engineering and the National Academy of Medicine, acknowledging her interdisciplinary impact.

Recent endeavors

In 2023, Li published a memoir titled “The Worlds I See: Curiosity, Exploration, and Discovery at the Dawn of AI,” offering insights into her personal journey and the evolution of artificial intelligence.

In 2024, Li co-founded World Labs, an AI company focusing on spatial intelligence and generative AI. The startup aims to develop AI systems capable of understanding and interacting with the three-dimensional physical world, with applications spanning robotics, autonomous vehicles, and augmented reality. World Labs quickly garnered significant investment, reflecting the growing interest in advanced AI technologies.

Advocacy and human-centered AI

Li is a strong advocate for ethical AI development and has worked with policymakers to ensure that AI technologies progress in a manner that benefits society. She has testified before U.S. Senate and Congressional committees, served as a special advisor to the Secretary-General of the United Nations, and was a member of the National Artificial Intelligence Research Resource Task Force for the White House Office of Science and Technology Policy.

Her focus on human-centered AI emphasizes the importance of developing technologies that are ethical, transparent, and aligned with human values, ensuring that the benefits of AI are widely shared across society.