Auvergne-Rhone-Alpes, France

Bingbing Wu

USPTO Granted Patents = 1 

Average Co-Inventor Count = 3.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: The Innovative Mind of Bingbing Wu

Introduction

Bingbing Wu is a prominent inventor based in Auvergne-Rhone-Alpes, France. She has made significant contributions to the field of robotics and skill learning through her innovative patent. Her work focuses on developing systems and methods that enhance the capabilities of robotic devices.

Latest Patents

Bingbing Wu holds a patent titled "Systems and methods for skill learning with multiple critics." This patent discloses a method for determining a policy to recommend transitions in a position-representing space for a robotic device using a multi-critic architecture. The approach involves defining a set of critics, each corresponding to different objective functions such as reach-reward, discovery-reward, and safety-reward. The policy is learned based on the weighted feedback of the learned value functions, ensuring safe transitions in the position-representing space. This innovative architecture minimizes interference between multiple reward functions, allowing for the development of a safe and stable policy for robotic devices. She has 1 patent to her name.

Career Highlights

Bingbing Wu is currently employed at Naver Corporation, where she continues to push the boundaries of robotic technology. Her work has garnered attention for its practical applications and innovative approach to skill learning in robotics.

Collaborations

Throughout her career, Bingbing has collaborated with talented individuals such as David Emukpere and Julien Perez. These collaborations have contributed to the advancement of her research and the successful implementation of her ideas.

Conclusion

Bingbing Wu is a trailblazer in the field of robotics, with her innovative patent showcasing her expertise in skill learning. Her contributions are paving the way for safer and more efficient robotic systems.

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