Bingsheng Wei

Fudan University, University of Shanghai for Science and Technology

Papers

Total Citations

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About

Bingsheng Wei is a researcher at the forefront of embodied artificial intelligence and robotic co-design, with a focus on the intricate interplay between robot morphology and control. His work addresses one of the most challenging problems in evolutionary robotics: jointly optimizing both the body and brain of a robot, particularly for designs that must transition from simulation to the real world. In his highly cited 2023 paper, Wei systematically evaluated frameworks that combine evolution with learning algorithms to navigate complex morphological spaces, providing critical insights into how robots can be more effectively designed and adapted. This work has garnered 17 citations, establishing a foundation for future research in scalable robot design. More recently, Wei has expanded into human-robot interaction, developing a depth residual contraction network that fuses sEMG and IMU signals for robust gait recognition in lower-limb exoskeletons. This research directly addresses the challenges of low accuracy and poor robustness in human-computer interaction, aiming to enhance assistive technologies for mobility-impaired individuals. Wei’s contributions bridge evolutionary robotics and wearable robotics, demonstrating a commitment to both theoretical frameworks and practical, real-world applications.