Welcome to the Stanford AI Lab! The Stanford Artificial Intelligence Laboratory (SAIL) has been a center of excellence for Artificial Intelligence research, teaching, theory, and practice since its founding in 1962. For more information, please download the pdf of our brochure.
Professor Salisbury student Shenli Yuan and Team Win ICRA 2020 Best Paper Awards
Congratulations to Shenli Yuan, Austin Epps, Jerome Nowak, and Kenneth Salisbury for winning the Best Student Paper Award and the Best Paper Award in Robot Manipulation at ICRA 2020!
SAIL Chirpy Cardinal Wins Second Place in the Alexa Prize
Congratulations to the SAIL Chirpy Cardinal for winning second place in the Alexa Prize. The team was led by PhD students Ashwin Paranjape and Abigail See along with faculty advisor and SAIL Director Christopher Manning.
Mike Wu and Team Win the AAAI 2019 Outstanding Student Paper Award
Congratulations to Mike Wu, Millan Mosse, Noah Goodman, and Chris Piechand for winning the AAAI 2019 outstanding student paper award!
Prof. Bohg Receives RSS 2020 Early Career Award
Congratulations to Prof. Bohg for earning an RSS 2020 Early Career Award!
Prof. Fei-Fei Li Elected to NAE
Congratulations to Prof. Fei-Fei Li for her election to the 2020 class of the National Academy of Engineering.
Prof. Dan Jurafsky Elected to AAAS
Congratulations to Prof. Dan Jurafsky for his 2020 election to the American Academy of Arts and Sciences.
2019 Technical Leadership Abie Award
Congratulations to Prof. Fei-Fei Li for her 2019 Technical Leadership Abie Awar presented by Anita Borg organization at the Grace Hopper Conference.
Best Paper Awards
SAIL best paper awards highlights:
ICCV 2019 best paper runner ups:
- Chengxu Zhuang, Alex Zhai, Daniel Yamins: Local aggregation for Unsupervised Learning of Visual Embeddings
- Charles R. Qi, Or Litany, Kaiming He, Leonidas Guibas: Deep Hough Voting for 3D Object Detection in Point Clouds
ICRA 2019 best paper:
- Michelle A. Lee, Yuke Zhu, Krishnan Srinivasan, Parth Shah, Silvio Savarese, Li Fei-Fei, Animesh Garg, Jeannette Bohg. Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks. Best paper award at ICRA 2019.
We are pleased to welcome two new faculty (1) Tatsunori Hashimoto who focuses on statistical tools to make machine learning systems more robust and reliable — especially in challenging tasks involving natural language; and (2) Jiajun Wu who studies machine perception, reasoning, and its interaction with the physical world, drawing inspiration from human cognition.
SAIL Affiliates News
The Stanford Computer Forum and CS Industry Affiliates Annual Meeting will be held virtually August 11 – 13, 2020.
This Annual Meeting will be co-hosted by SDSI, AI Safety, SAIL, and the Stanford Computer Forum. The three-day event will present opportunities for our industrial partners to hear about latest developments in timely and critical areas of technology. As in previous years, we look forward to sharing new faculty research and advances in big data, machine learning, reinforcement learning and natural language processing.
To register please click here and use the registration password: signmeup2020
SAIL Affiliates Program Welcomes Newest Member: Total
The SAIL Affiliates Program is pleased to welcome Total, a global leader in oil and gas exploration, production, power generation, transportation, refining, marketing, and trading with more than 900 subsidiaries operating in over 130 countries.