Eric Anthony Mitchell
Ph.D. Student, Stanford University

I am currently a third-year PhD student in Stanford’s CS department, where I’m fortunate to be advised by Chelsea Finn and Chris Manning. The goal of my research is to make the knowledge embedded in neural networks more reusable and updatable in an ever-changing world. I think a lot about meta-learning and continual learning, particularly in large neural networks. I am grateful to be supported by a Knight-Hennessy Graduate Fellowship.

You can find my CV here.

Earlier, I was a research engineer at Samsung’s AI Center in New York City, where I learned constantly from Volkan Isler, Daniel D. Lee, and many other wonderful (and patient) people. As an undergraduate, I completed my thesis under the guidance of H. Sebastian Seung after many hours in the Seung Lab at the Princeton Neuroscience Institute. I also competed for Princeton’s varsity men’s golf team.

In my free time, I make music for guitar and voice. I enjoy the outdoors, particularly golf courses and mountains.

Recent Papers

See Google Scholar for the latest
Fast Model Editing at Scale, 2022, ICLR
Eric A Mitchell , Charles Lin , Antoine Bosselut , Chelsea Finn , Christopher D Manning
Learning Language-Conditioned Robot Behavior from Offline Data and Crowd-Sourced Annotation, 2022, CoRL
Suraj Nair , Eric A Mitchell , Kevin Chen , Brian Ichter , Silvio Savarese , Chelsea Finn
On the Opportunities and Risks of Foundation Models, 2021, Whitepaper
Stanford Center for Research on Foundation Models
Petascale Neural Circuit Reconstruction: Automated Methods, 2021, Preprint
Sven Dorkenwald et al.
Offline Meta-Reinforcement Learning with Advantage Weighting, 2021, ICML
Eric A Mitchell , Rafael Rafailov , Xue Bin Peng , Sergey Levine , Chelsea Finn
Geodesic-HOF: 3D Reconstruction Without Cutting Corners, 2021, AAAI
Ziyun Wang , Eric A Mitchell , Volkan Isler , Daniel D Lee
Higher Order Function Networks for View Planning and Multi-View Reconstruction, 2020, ICRA
Selim Engin , Eric A Mitchell , Daewon Lee , Volkan Isler , Daniel D Lee
Higher-Order Function Networks for Learning Composable 3D Object Representations, 2020, ICLR
Eric A Mitchell , Selim Engin , Volkan Isler , Daniel D Lee