Papers

8

Total Citations

135

H-Index

6

About

Huawei Wang is a leading researcher at the intersection of biomechanics, motor control, and rehabilitation robotics, with a core focus on developing high-fidelity computational tools to bridge the gap between biological systems and robotic assistive devices. His most significant contribution is the creation of **MyoSim** and **MyoSuite**—a family of fast, physiologically realistic musculoskeletal simulation models built on the MuJoCo physics engine. These platforms, which have collectively garnered over 100 citations since 2022, enable researchers to study complex, contact-rich motor control tasks that were previously impossible to simulate, opening new avenues for motor learning and neurorehabilitation research. Wang’s work is distinguished by its human-centred design philosophy, as seen in his narrative review on tapping into skeletal muscle biomechanics for lower limb exoskeleton control and his contributions to the EU-funded SOPHIA project. By integrating stochastic trajectory optimization for postural control identification and developing novel calibration methods for inertial-visual sensing, Wang provides the foundational tools and biomechanical insights necessary to design smarter, safer exoskeletons and robotic rehabilitation systems that work in harmony with human physiology.

Research Focus

Key Achievements

6
H-Index
8
Papers
135
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
MyoSim: Fast and physiologically realistic MuJoCo models for musculoskeletal and exoskeletal studies
48 citations · 2022
📈 Most Prolific Year: 2022 (5 Papers)
🤝 Key Collaborators: 19
🏛 Institutions: University of Twente, Cleveland State University, PLA Electronic Engineering Institute

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago