Max Robotics — Global Service Robot Directory + US Certification

About

Nina Zeng is a rising leader in orthopaedic surgery, whose research focuses on optimizing outcomes in robotic-arm assisted knee arthroplasty. Her work critically examines the integration of advanced surgical technologies, particularly the learning curves and operative efficiencies associated with these systems. In a landmark 2022 study, she demonstrated that robotic-arm assisted total knee arthroplasty has a learning curve of 16 cases and increases operative time by 12 minutes, providing essential benchmarks for surgical adoption. Her prospective randomized controlled trial comparing mechanical axis alignment with functional alignment in robotic-assisted total knee replacement has garnered significant attention for its rigorous methodology and implications for improving functional outcomes. Zeng has also defined the learning curve for unicompartmental knee arthroplasty at 11 cases, offering guidance for surgeons transitioning to robotic systems. With her most cited papers accumulating over 70 citations in just a few years, her work is already shaping best practices in orthopaedics. Zeng’s contributions are vital for surgeons and researchers seeking to balance technological innovation with practical, patient-centered care.