Max Robotics — Global Service Robot Directory + US Certification

About

Wenjing Li is a pioneering researcher at the intersection of robotics, biomechanics, and intelligent systems, whose work bridges fundamental engineering challenges with real-world applications. Her primary research areas include physics-informed neural networks, magnetic actuation systems, and service robotics, with a particular focus on developing compliant, energy-efficient mechanisms for human-robot interaction. Li’s most impactful contribution is her 2021 paper on physics-informed neural networks for parameter identification and boundary force estimation in compliant systems (20 citations), which introduced a novel computational framework for modeling biomechanical structures without extensive training data. She also made significant strides in practical robotics with her 2020 design of a mobile garbage collection robot using visual recognition (17 citations), demonstrating autonomous navigation and object detection capabilities. More recently, Li’s work on magnetic leadscrews with embedded displacement sensors (2023) and spring-like magnetic energy for elastic actuation (2023) has advanced the development of wear-free transmission systems and nonlinear stiffness actuators for safe human-robot collaboration. Her innovative approach to integrating wireless sensing with physics-based neural networks (2025) further showcases her commitment to creating intelligent, self-sensing robotic systems. With a growing citation footprint and a portfolio spanning from theoretical modeling to deployable prototypes, Li is establishing herself as a versatile engineer whose work directly addresses the demands of next-generation assistive and service robotics.