Chelsea Finn
cbfinn at cs dot stanford dot edu

I am an Assistant Professor in Computer Science and Electrical Engineering at Stanford University. My lab, IRIS, studies intelligence through robotic interaction at scale, and is affiliated with SAIL and the ML Group. I also spend time at Google as a part of the Google Brain team.

I am interested in the capability of robots and other agents to develop broadly intelligent behavior through learning and interaction.

Previously, I completed my Ph.D. in computer science at UC Berkeley and my B.S. in electrical engineering and computer science at MIT.

CV  /  Bio  /  PhD Thesis  /  Google Scholar  /  Twitter  /  IRIS Lab

See our lab website for up-to-date news.

• Our work on meta-learning for giving feedback to students was featured in the New York Times. See the blog post, paper, and slides for more information.
• I am honored to have received Intel's Rising Star Faculty Award and the Microsoft Faculty Fellowship award.
• In Fall 2019, I taught a new course on deep multi-task and meta learning. Lecture videos are available here.
• I am honored and thrilled to have received the ACM 2018 Doctoral Dissertation Award for my thesis, Learning to Learn with Gradients.
• Our work on enabling robots to use objects as tools was featured in an article by MIT Technology Review
• I am honored to have received the MIT TR35 pioneer award.
• In August 2018, I completed my PhD!
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Some of my research was featured in a TechCrunch article.
At NIPS 2017, we showcased our research on meta-imitation learning and visual foresight in a live robot demo! For more information and a video, see this page.
In summer 2017, I co-organized BAIR camp, a 2-day summer camp on human-centered AI for high-school students from low income backgrounds. We are organizing a second camp in August 2018.
In Spring 2017, I helped develop and co-taught a course on deep reinforcement learning.
I co-organized a workshop at NIPS 2016 on Deep Learning for Action and Interaction (videos here).
My colleagues and I have released the robotic grasping and pushing data used in Levine et al. '16 (ISER) and Finn et al. '16 (NIPS): Google Brain Robotics Data.

See this page for a list of lab members.

Stanford CS224R: Deep Reinforcement Learning - Spring 2023
Stanford CS330: Deep Multi-Task and Meta Learning - Fall 2019, Fall 2020, Fall 2021, Fall 2022
Stanford CS221: Artificial Intelligence: Principles and Techniques - Spring 2020, Spring 2021
UCB CS294-112: Deep Reinforcement Learning - Spring 2017