Sotabase

Career

· Visiting Professor, NVIDIA2024–
· Assistant Professor, University of Washington2022–
· Postdoctoral Researcher, Massachusetts Institute of Technology (MIT)2021–2022
· Research Intern, Google Brain Robotics2019–
· Research Assistant, UC Berkeley2015–2021
· PhD in Computer Science, University of California, Berkeley2015–2021
· PhD Student, University of California, Berkeley2015–2021
· Research Assistant, UC Berkeley2014–2015
· Software Development Engineering Intern, Motorola Solutions Inc.2013–
· Web Development Engineering Intern, EdX Berkeley2012–
· B.S. in Electrical Engineering and Computer Sciences, University of California, Berkeley2011–2015

Publications (0)

Soft Actor-Critic Algorithms and Applications
arXiv.org · 2018
2,917
cited
Gradient Surgery for Multi-Task Learning
Neural Information Processing Systems · 2020
1,564
cited
Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations
Robotics: Science and Systems · 2017
1,276
cited
Diversity is All You Need: Learning Skills without a Reward Function
International Conference on Learning Representations · 2018
1,217
cited
Accelerating Online Reinforcement Learning with Offline Datasets
arXiv.org · 2020
735
cited
Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning
Conference on Robot Learning · 2019
516
cited
DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
Robotics: Science and Systems · 2024
512
cited
Learning modular neural network policies for multi-task and multi-robot transfer
IEEE International Conference on Robotics and Automation · 2016
429
cited
Imitation from Observation: Learning to Imitate Behaviors from Raw Video via Context Translation
IEEE International Conference on Robotics and Automation · 2017
406
cited
Meta-Reinforcement Learning of Structured Exploration Strategies
Neural Information Processing Systems · 2018
371
cited
The Stanford FLASH multiprocessor
Proceedings of 21 International Symposium on Computer Architecture · 1994
362
cited
Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration
IEEE International Conference on Robotics and Automation · 2024
282
cited
Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning
International Conference on Learning Representations · 2017
281
cited
AI Art and its Impact on Artists
AAAI/ACM Conference on AI, Ethics, and Society · 2023
263
cited
Adaptive Risk Minimization: Learning to Adapt to Domain Shift
Neural Information Processing Systems · 2020
246
cited
Guiding Pretraining in Reinforcement Learning with Large Language Models
International Conference on Machine Learning · 2023
231
cited
Optimal control in the presence of an intelligent jammer with limited actions
IEEE Conference on Decision and Control · 2010
228
cited
Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost
IEEE International Conference on Robotics and Automation · 2018
219
cited
Learning to Reach Goals via Iterated Supervised Learning
International Conference on Learning Representations · 2019
208
cited
Development of a balanced scorecard
2006
202
cited
Sotabase