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Reading group

We have several weekly reading groups where we present and discuss papers on various topics in machine learning, natural language processing, computer vision, etc. This one is from the ML reading group.

Reading group

We have several weekly reading groups where we present and discuss papers on various topics in machine learning, natural language processing, computer vision, etc.

Lunches

Every week, different research areas get together for lunch with research talks. This is the natural language processing (NLP) group.

Stanford AI Lab's Outreach

Stanford AI4ALL is designed to expose high school students in underrepresented populations to the field of Artificial Intelligence (AI).

Interdisciplinary research

The AI Lab brings together faculty and students from a variety of disciplines. This picture shows students from the Department of Computer Science and the Department of Aeronautics and Astronautics working together to build a distributed conflict avoidance system for unmanned aircraft.

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.

Recent News

SAIL and GSB Human-Centered AI Call for Proposals

The Stanford AI Lab and the Graduate School of Business would like to request seed proposals from students, faculty and research staff. These proposals will be funded through generous gift donations and affiliate program membership fees. This call for proposals aims to support innovative and interdisciplinary seed research in Human-centered Artificial Intelligence with preference for funding interdepartmental collaborations. For more information, please download the pdf. We welcome your questions and proposals!

Best Paper Awards

SAIL won a number of best paper awards this year:

Hongseok Namkoong, John Duchi. Variance-based Regularization with Convex Objectives. Best paper award at NIPS 2017.
Amy Jin, Serena Yeung, Jeffrey Jopling, Jonathan Krause, Dan Azagury, Arnold Milstein, and Li Fei-Fei. Tool Detection and Operative Skill Assessment in Surgical Videos Using Region-Based Convolutional Neural Networks. Best paper award at the NIPS 2017 Machine Learning for Health workshop.
Pang Wei Koh, Percy Liang. Understanding Black-box Predictions via Influence Functions. Best paper award at ICML 2017.
Shayan Doroudi, Philip S. Thomas, Emma Brunskill. Importance Sampling for Fair Policy Selection. Best paper award at UAI 2017.
Yuchen Zhang, Percy Liang, Moses Charikar. A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics. Best paper award at COLT 2017.
Russell Stewart, Stefano Ermon. Label-Free Supervision of Neural Networks with Physics and Domain Knowledge. Outstanding paper award at AAAI 2017.

SAIL announces new research initiative funded by JD.com

SAIL is delighted to announce that JD.com, China’s largest retailer has agreed to establish the SAIL JD AI Research Initiative, a sponsored research program at the Stanford Artificial Intelligence Lab. The collaboration will fund research into a range of areas including natural language processing, computer vision, robotics, machine learning, deep learning, reinforcement learning, and forecasting.

New Faculty

We are pleased to have three new faculty — Dorsa Sadigh, Jeannette Bohg, Emma Brunskill — joining us, greatly increasing our strength in robotics and reinforcement learning. Tengyu Ma will join next year with a joint appointment in statistics.

SAIL Affiliates Program Welcomes Newest Member: Google and DiDi

The SAIL Affiliates Program is pleased to welcome Google, the largest internet-related technology company providing advertising, search, cloud computing, software, and hardware technologies and, DiDi, a major ride-sharing company that provides transportation services for close to 400 million users across over 400 cities in China. Google and DiDi joins existing members: Panasonic, UST Global, Tencent, Samsung, and Oppo.