Li at AI for Good in 2017
|Born||1976 (age 44–45)|
|Alma mater||Princeton University (B.A. in Physics)|
California Institute of Technology (2005, PhD)
|Known for||Computer vision |
|Awards||Paul and Daisy Soros Fellowship for New Americans (1999), Microsoft Research New Faculty Fellowship (2006), Sloan Fellowship (2011), J.K. Aggarwal Prize, International Association for Pattern Recognition (IAPR) (2016), One of the 40 “The great immigrants,” Carnegie Foundation (2016), ACM Fellow for "contributions in building large knowledge bases for machine learning and visual understanding" (2018)|
|Institutions||Stanford University |
|Thesis||Visual Recognition: Computational Models and Human Psychophysics (2005)|
|Doctoral advisor||Pietro Perona|
|Doctoral students||Olga Russakovsky |
Fei-Fei Li (simplified Chinese: 李飞飞; traditional Chinese: 李飛飛; born 1976) is a Chinese-born American computer scientist, non-profit executive, and writer. She is the Sequoia Capital Professor of Computer Science at Stanford University. Li is a Co-Director of the Stanford Institute for Human-Centered Artificial Intelligence, and a Co-Director of the Stanford Vision and Learning Lab. She served as the director of the Stanford Artificial Intelligence Laboratory (SAIL) from 2013 to 2018. In 2017, she co-founded AI4ALL, a nonprofit organization working to increase diversity and inclusion in the field of artificial intelligence. Her research expertise includes artificial intelligence (AI), machine learning, deep learning, computer vision and cognitive neuroscience. She was the leading scientist and principal investigator of ImageNet.
Early life and education
Li was born in Beijing, China in 1976 and grew up in Chengdu. When she was 12, her father moved to the US; when she was 16, she and her mother joined him in Parsippany-Troy Hills, New Jersey. She graduated from Parsippany High School in 1995, where she was inducted to the Hall of Fame of Parsippany High School in 2017.
Li majored in physics but also studied computer science and engineering as an undergraduate student at Princeton University, from where she graduated with high honors with an A.B. in physics and certificates in applied and computational mathematics and engineering physics in 1999. Li completed her senior thesis, titled "Auditory Binaural Correlogram Difference: A New Computational Model for Huggins Dichotic Pitch", under the supervision of Professor of Electrical Engineering Bradley Dickinson. During her years at Princeton, she returned home most weekends so that she could work in her parents' dry-cleaning store.
Li then pursued graduate studies at the California Institute of Technology, where she received a Ph.D. in electrical engineering in 2005. Li completed her dissertation, titled "Visual Recognition: Computational Models and Human Psychophysics", under the primary supervision of Pietro Perona and secondary supervision of Christof Koch. Her graduate studies were supported by the National Science Foundation Graduate Research Fellowship and The Paul & Daisy Soros Fellowships for New Americans.
From 2005 to August 2009, Li was an assistant professor in the Electrical and Computer Engineering Department at University of Illinois Urbana-Champaign and Computer Science Department at Princeton University, respectively. She joined Stanford in 2009 as an assistant professor, and was promoted to associate professor with tenure in 2012, and then full professor in 2017. At Stanford, Li served as the director of Stanford Artificial Intelligence Lab (SAIL) from 2013 to 2018. She became the founding co-director of Stanford's University-level initiative - the Human-Centered AI Institute, along with co-director Dr. John Etchemendy, former provost of Stanford University.
On her sabbatical from Stanford University from January 2017 to fall of 2018, Li joined Google Cloud as its Chief Scientist of AI/ML and Vice President. At Google, her team focuses on democratizing AI technology and lowering the barrier for entrance to businesses and developers, including the developments of products like AutoML. She returned to Stanford University to continue her professorship in the fall of 2018.
Li is also known for her nonprofit work as the co-founder and chairperson of nonprofit organization AI4ALL, whose mission is to educate the next generation of AI technologists, thinkers and leaders by promoting diversity and inclusion through human-centered AI principles. Prior to establishing AI4ALL in 2017, Li and her former student Olga Russakovsky, currently an assistant professor in Princeton University, co-founded and co-directed the precursor program at Stanford called SAILORS (Stanford AI Lab OutReach Summers). SAILORS was an annual summer camp at Stanford dedicated to 9th grade high school girls in AI education and research, established in 2015 till it changed its name to AI4ALL @Stanford in 2017. In 2018, AI4ALL has successfully launched five more summer programs in addition to Stanford, including Princeton University, Carnegie Mellon University, Boston University, U. of California Berkeley, and Canada's Simon Fraser University.
Li has been described as an "AI pioneer" and a "researcher bringing humanity to AI".
Li works on AI, machine learning, computer vision, cognitive neuroscience and computational neuroscience. She has published nearly 180 peer-reviewed research papers. Her work appears in computer science and neuroscience journals including Nature, Proceedings of the National Academy of Sciences, Journal of Neuroscience, Conference on Computer Vision and Pattern Recognition, International Conference on Computer Vision, Conference on Neural Information Processing Systems, European Conference on Computer Vision, International Journal of Computer Vision, and IEEE Transactions on Pattern Analysis and Machine Intelligence. Among her best-known work is the ImageNet project, which has revolutionized the field of large-scale visual recognition.
Li has led the team of students and collaborators to organize the international competition on ImageNet recognition tasks called ImageNet Large-Scale Visual Recognition Challenge (ILSVRC) between 2010 and 2017 in the academic community.
Li's research in computer vision contributed significantly to a line of work called Natural Scene Understanding, or later, Story-telling of images. She is a recognized for her work in this area by the International Association for Pattern Recognition in 2016. She delivered a talk on the main stage of TED in Vancouver in 2015, and has since then been viewed more than 2 million times.
In recent years, Fei-Fei Li's research work expanded to AI and Healthcare, collaborating closely with Prof. Arnold Milstein at Stanford, a recognized national leader working in improving healthcare delivery.
She has taught the Stanford course CS231n on "Convolutional Neural Nets for Visual Recognition." It is also on Coursera, a popular online learning platform founded by her Stanford colleagues Daphne Koller and Andrew Ng.
Selected honors and distinctions
- 1999 Paul and Daisy Soros Fellowship for New Americans 
- 2006 Microsoft Research New Faculty Fellowship 
- 2009 NSF CAREER Award 
- 2010 Best Paper Honorable Mention, IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 
- 2011 Fellow, Alfred P. Sloan Fellowship 
- 2015 One of the Leading Global Thinkers of 2015, Foreign Policy 
- 2016 IEEE PAMI Mark Everingham Prize [reference link]
- 2016 J.K. Aggarwal Prize, International Association for Pattern Recognition (IAPR) 
- 2016 One of the 40 “The great immigrants,” Carnegie Foundation 
- 2017 WITI@UC Athena Award for Academic Leadership, University of California 
- 2017 One of Seven Women in Technology honorees, Elle Magazine 
- 2018 Elected as ACM Fellow for "contributions in building large knowledge bases for machine learning and visual understanding"
- 2018 "America's Top 50 Women In Tech" by Forbes
- 2018 U.S. Congressional hearing by Subcommittee on Research and Technology & Subcommittee on Energy 
- 2019 Technical Leadership Abie Award Winner, AnitaB.org
- Markoff, John (November 19, 2012). "Seeking a Better Way to Find Web Images". The New York Times.
Dr. Li, 36
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