Xue Bin (Jason) Peng

I'm an Assistant Professor at Simon Fraser University (SFU) and a Research Scientist at NVIDIA. I received a Ph.D. from UC Berkeley, advised by Professor Sergey Levine and Professor Pieter Abbeel. Prior to that, I received an M.Sc from the University of British Columbia, advised by Professor Michiel van de Panne. My work lies in the intersection between computer graphics and machine learning, with a focus on reinforcement learning for motion control of simulated characters. I have previously worked for Sony, Google Brain, OpenAI, Adobe Research, Disney Research, Microsoft (343 Industries), and Capcom.

Prospective students: Information is available here.



Publications

  — 2022 —

Creating a Dynamic Quadrupedal Robotic Goalkeeper with Reinforcement Learning
Xiaoyu Huang, Zhongyu Li, Yanzhen Xiang, Yiming Ni, Yufeng Chi, Yunhao Li, Lizhi Yang, Xue Bin Peng, and Koushil Sreenath
arXiv Preprint 2022
[Project page] [Paper]
Hierarchical Reinforcement Learning for Precise Soccer Shooting Skills using a Quadrupedal Robot
Yandong Ji, Zhongyu Li, Yinan Sun, Xue Bin Peng, Sergey Levine, Glen Berseth, Koushil Sreenath
arXiv Preprint 2022
[Project page] [Paper]
GenLoco: Generalized Locomotion Controllers for Quadrupedal Robots
Gilbert Feng, Hongbo Zhang, Zhongyu Li, Xue Bin Peng, Bhuvan Basireddy, Linzhu Yue, Zhitao Song, Lizhi Yang, Yunhui Liu, Koushil Sreenath, Sergey Levine
Conference on Robot Learning (CORL 2022)
[Project page] [Paper]
ASE: Large-Scale Reusable Adversarial Skill Embeddings for Physically Simulated Characters
Xue Bin Peng, Yunrong Guo, Lina Halper, Sergey Levine, Sanja Fidler
ACM Transactions on Graphics (Proc. SIGGRAPH 2022)
[Project page] [Paper]
Adversarial Motion Priors Make Good Substitutes for Complex Reward Functions
Alejandro Escontrela, Xue Bin Peng, Wenhao Yu, Tingnan Zhang, Atil Iscen, Ken Goldberg, Pieter Abbeel
arXiv Preprint 2022
[Project page] [Paper]
CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery
Michael Laskin, Hao Liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran, Pieter Abbeel
arXiv Preprint 2022
[Project page] [Paper]
Legged Robots that Keep on Learning: Fine-Tuning Locomotion Policies in the Real World
Laura Smith, J. Chase Kew, Xue Bin Peng, Sehoon Ha, Jie Tan, Sergey Levine
IEEE International Conference on Robotics and Automation (ICRA 2022)
[Project page] [Paper]

  — 2021 —

Deep Reinforcement Learning for Modeling Human Locomotion Control in Neuromechanical Simulation
Seungmoon Song, Łukasz Kidziński, Xue Bin Peng, Carmichael Ong, Jennifer Hicks, Sergey Levine, Christopher G. Atkeson, Scott L. Delp
Journal of NeuroEngineering and Rehabilitation 2021
[Project page] [Paper]
Offline Meta-Reinforcement Learning with Advantage Weighting
Eric Mitchell, Rafael Rafailov, Xue Bin Peng, Sergey Levine, Chelsea Finn
International Conference on Machine Learning (ICML 2021)
[Project page] [Paper]
AMP: Adversarial Motion Priors for Stylized Physics-Based Character Control
Xue Bin Peng, Ze Ma, Pieter Abbeel, Sergey Levine, Angjoo Kanazawa
ACM Transactions on Graphics (Proc. SIGGRAPH 2021)
[Project page] [Paper]
Reinforcement Learning for Robust Parameterized Locomotion Control of Bipedal Robots
Zhongyu Li, Xuxin Cheng, Xue Bin Peng, Pieter Abbeel, Sergey Levine, Glen Berseth, Koushil Sreenath
IEEE International Conference on Robotics and Automation (ICRA 2021)
[Project page] [Paper]

  — 2020 —

Learning Agile Robotic Locomotion Skills by Imitating Animals
Xue Bin Peng, Erwin Coumans, Tingnan Zhang, Tsang-Wei Edward Lee, Jie Tan, Sergey Levine
Robotics: Science and Systems (RSS 2020)
Best Paper Award
[Project page] [Paper]
Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives
Anirudh Goyal, Shagun Sodhani, Jonathan Binas, Xue Bin Peng, Sergey Levine, Yoshua Bengio
International Conference on Learning Representations (ICLR 2020)
[Project page] [Paper]

  — 2019 —

Reward-Conditioned Policies
Aviral Kumar, Xue Bin Peng, Sergey Levine
arXiv Preprint 2019
[Project page] [Paper]
On Learning Symmetric Locomotion
Farzad Adbolhosseini, Hung Yu Ling, Zhaoming Xie, Xue Bin Peng, Michiel van de Panne
ACM SIGGRAPH Conference on Motion, Interaction, and Games (MIG 2019)
[Project page] [Paper]
Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning
Xue Bin Peng, Aviral Kumar, Grace Zhang, Sergey Levine
arXiv Preprint 2019
[Project page] [Paper]
MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies
Xue Bin Peng, Michael Chang, Grace Zhang, Pieter Abbeel, Sergey Levine
Neural Information Processing Systems (NeurIPS 2019)
[Project page] [Paper]
Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow
Xue Bin Peng, Angjoo Kanazawa, Sam Toyer, Pieter Abbeel, Sergey Levine
International Conference on Learning Representations (ICLR 2019)
[Project page] [Paper]

  — 2018 —

SFV: Reinforcement Learning of Physical Skills from Videos
Xue Bin Peng, Angjoo Kanazawa, Jitendra Malik, Pieter Abbeel, Sergey Levine
ACM Transactions on Graphics (Proc. SIGGRAPH Asia 2018)
[Project page] [Paper]
DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills
Xue Bin Peng, Pieter Abbeel, Sergey Levine, Michiel van de Panne
ACM Transactions on Graphics (Proc. SIGGRAPH 2018)
[Project page] [Paper]
Sim-to-Real Transfer of Robotic Control with Dynamics Randomization
Xue Bin Peng, Marcin Andrychowicz, Wojciech Zaremba, Pieter Abbeel
IEEE International Conference on Robotics and Automation (ICRA 2018)
[Project page] [Paper]

  — 2017 —

DeepLoco: Developing Locomotion Skills Using Hierarchical Deep Reinforcement Learning
Xue Bin Peng, Glen Berseth, KangKang Yin, Michiel van de Panne
ACM Transactions on Graphics (Proc. SIGGRAPH 2017)
[Project page] [Paper]
Learning Locomotion Skills Using DeepRL: Does the Choice of Action Space Matter?
Xue Bin Peng, Michiel van de Panne
ACM SIGGRAPH / Eurographics Symposium on Computer Animation 2017
Best Student Paper Award
[Project page] [Paper]

  — 2016 —

Terrain-Adaptive Locomotion Skills Using Deep Reinforcement Learning
Xue Bin Peng, Glen Berseth, Michiel van de Panne
ACM Transactions on Graphics (Proc. SIGGRAPH 2016)
[Project page] [Paper]

  — 2015 —

Dynamic Terrain Traversal Skills Using Reinforcement Learning
Xue Bin Peng, Glen Berseth, Michiel van de Panne
ACM Transactions on Graphics (Proc. SIGGRAPH 2015)
[Project page] [Paper]




Thesis


Ph.D. Thesis
Acquiring Motor Skills Through Motion Imitation and Reinforcement Learning
University of California, Berkeley 2021
[Project page] [Thesis]
M.Sc. Thesis
Developing Locomotion Skills with Deep Reinforcement Learning
University of British Columbia 2017
[Project page] [Thesis]