Coline Devin

I am a senior research scientist at DeepMind. I completed my PhD in 2020 at UC Berkeley, advised by Professors Sergey Levine, Pieter Abbeel and Trevor Darrell, and supported by the NSF Graduate Research Fellowship. I have previously interned at OSARO, Google Brain, and DeepMind. I completed my B.S. in Computer Science at Harvey Mudd College.

Google Scholar / GitHub / Dissertation Talk

email: [firstname].[lastname][at]gmail.com

Talks

5th Inter-experiment Machine Learning Workshop and EP-IT Data science seminar: Beyond Pick and Place - Tackling Robotic Stacking of Diverse Shapes. 2022

Research and Applied AI Summit: Modularity for Robot Learning. 2019

Research

My research is robot learning, with an emphasis on approaches that can show compositionality and generality in tasks, objects, and environments.

	How to Spend Your Robot Time: Bridging Kickstarting and Offline Reinforcement Learning for Vision-based Robotic Manipulation Alex X Lee, Coline Devin, Jost Tobias Springenberg, Yuxiang Zhou, Thomas Lampe, Abbas Abdolmaleki, Konstantinos Bousmalis IROS 2022* arxiv
	Beyond pick-and-place: Tackling robotic stacking of diverse shapes Alex X Lee, Coline Devin, Yuxiang Zhou, Thomas Lampe, Konstantinos Bousmalis, Jost Tobias Springenberg, Arunkumar Byravan, Abbas Abdolmaleki, Nimrod Gileadi, David Khosid, Claudio Fantacci, Jose Enrique Chen, Akhil Raju, Rae Jeong, Michael Neunert, Antoine Laurens, Stefano Saliceti, Federico Casarini, Martin Riedmiller, Francesco Nori CoRL 2021 arxiv / blog / video
	Fully Autonomous Real-World Reinforcement Learning with Applications to Mobile Manipulation Charles Sun, Jȩdrzej Orbik, Coline Manon Devin, Brian H Yang, Abhishek Gupta, Glen Berseth, Sergey Levine CoRL 2021 arxiv
	SMiRL: Surprise Minimizing RL in Dynamic Environments Glen Berseth, Daniel Geng, Coline Devin, Chelsea Finn, Dinesh Jayaraman, Sergey Levine ICLR 2021 (Oral) arxiv / blog
	Learning To Reach Goals Without Reinforcement Learning Dibya Ghosh, Abhishek Gupta, Justin Fu, Ashwin Reddy, Coline Devin, Benjamin Eysenbach, Sergey Levine arxiv
	Plan Arithmetic: Compositional Plan Vectors for Multi-Task Control Coline Devin, Daniel Geng, Pieter Abbeel, Trevor Darrell, Sergey Levine NeurIPS 2019 arxiv / webpage / short video / code
	Monocular Plan View Networks for Autonomous Driving Dequan Wang, Coline Devin, Qi-Zhi Cai, Philipp Krahënbühl, Trevor Darrell IROS 2019 arxiv
	Deep Object Centric Policies for Autonomous Driving Dequan Wang, Coline Devin, Qi-Zhi Cai, Fisher Yu, Trevor Darrell ICRA 2019 arxiv
	Grasp2Vec: Learning Object Representations from Self-Supervised Grasping Eric Jang, Coline Devin, Vincent Vanhoucke, Sergey Levine * Denotes equal contribution CoRL 2018 arxiv / webpage / code
	Deep Object-Centric Representations for Generalizable Robot Learning Coline Devin, Pieter Abbeel, Trevor Darrell, Sergey Levine ICRA 2018 arxiv / webpage / code
	Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning Abhishek Gupta, Coline Devin, YuXuan Liu, Pieter Abbeel, Sergey Levine * Denotes equal contribution ICLR, 2017 webpage / video
	Learning Modular Neural Network Policies for Multi-Task and Multi-Robot Transfer Coline Devin, Abhishek Gupta, Trevor Darrell, Pieter Abbeel, Sergey Levine * Denotes equal contribution ICRA, 2017 arxiv / webpage / video
	Adapting deep visuomotor representations with weak pairwise constraints Eric Tzeng, Coline Devin, Judy Hoffman, Chelsea Finn, Pieter Abbeel, Sergey Levine, Kate Saenko, Trevor Darrell WAFR, 2016 arxiv

Website template from Jon Barron.
Last updated June 2022.