I am a Senior Staff Research Scientist and Tech Lead Manager in the robotics team of Google DeepMind. My research focuses on applying foundation models and deep reinforcement learning methods to robots, with interests spanning locomotion, navigation, manipulation, simulation, and sim-to-real transfer.

Jie Tan. Google DeepMind. Verified email at google.com - Homepage. Artificial General Intelligence Robotics Foundation Model Computer Graphics Vision. ... J Ibarz, J Tan, C Finn, M Kalakrishnan, P Pastor, S Levine. The International Journal of …

Learning agile locomotion via adversarial training, Yujin Tang, Jie Tan and Tatsuya Harada, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

2018年4月27日 · Designing agile locomotion for quadruped robots often requires extensive expertise and tedious manual tuning. In this paper, we present a system to automate this process by leveraging deep reinforcement learning techniques. Our system can learn quadruped locomotion from scratch using simple reward signals.

My research focused on developing computational tools to understand, simulate and control human and animal motions in a complex environment. I developed fast and stable computer programs to simulate complex dynamic systems, such as …

We develop a system for learning legged locomotion policies with deep RL in the real world with minimal human effort, using a multi-task learning procedure and a safety-constrained RL framework. [Paper Video] Learning Agile Locomotion via Adversarial Training. Yujin Tang, Jie Tan, Tatsuya Harada.

Jie Tan received the Ph.D. degree in computer science from the Georgia Institute of Technology, Atlanta, GA, USA, in 2015. He is currently a Staff Research Scientist with Google Research. His research interests include deep reinforcement learning and its application on real-world systems, including robotics, and power grid.

Proceedings of the 33rd ACM International Conference on Information and …

Jie Tan. Unsupervised situational assessment for power grid voltage stability monitoring based on Siameseautoencoder and k-Means clustering. International Conference on Artificial Intelligence and Security. 2020, [12] Li, Yaning, Wang, Xuelei, Tan, Jie.