Juan Ren

Iowa State University, Chang'an University

Papers

Total Citations

H-Index

About

Juan Ren is a pioneering researcher at the intersection of robotics, control theory, and nanoscale manipulation. Her work spans three critical domains: hybrid position/force control for joint robots, ultrawide-range torque sensing for micro/nanomaterials, and data-driven motion planning for medical nanorobots. In her 2021 paper on hybrid position/force controllers, Ren introduced a decoupling strategy that enables simultaneous motion tracking and force regulation, achieving 7 citations for its practical utility in industrial robotics. That same year, she advanced in situ SEM characterization with a robot-aided torque sensor capable of measuring forces across an ultrawide dynamic range (6 citations), enabling unprecedented torsion tests on micro/nanomaterials—a fundamental tool for material analytics. Most notably, her 2023 work on medical nanorobots (5 citations) addresses the formidable challenge of trajectory control at micron scales, integrating a Dynamic Window Approach with data-driven optimal control to ensure precise drug delivery. Ren’s contributions are particularly impactful for their ability to bridge theoretical control frameworks with real-world applications, from manufacturing to nanomedicine. Her research not only solves immediate engineering problems but also lays the groundwork for next-generation autonomous systems operating at the smallest scales.