Lulu Song

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About

Lulu Song is a researcher at the forefront of rehabilitation robotics, specializing in the intersection of biomechanics, humanoid control, and artificial intelligence. Her work focuses on developing intelligent lower limb rehabilitation exoskeletons that can restore mobility to patients with limb dysfunction. Song’s major contributions include pioneering musculoskeletal modeling and inverse dynamics analysis of human gait data, which provide the foundational biomechanical insights necessary for designing robots that move in harmony with the human body. She has also advanced human-robot cooperation by applying deep learning to predict gait trajectories, enabling exoskeletons to anticipate and assist a wearer’s intended movement. Her most cited work, “Musculoskeletal modeling and humanoid control of robots based on human gait data” (2021), has garnered 20 citations and is recognized for its role in bridging the gap between human physiology and robotic control. Through her research, Song is directly addressing the challenge of creating bio-inspired controllers that can effectively aid in rehabilitation training, making her a key contributor to the development of more responsive and effective assistive technologies for patients with lower limb disorders.