Sisi Zhang

Shandong University, RWTH Aachen University

Papers

Total Citations

115

H-Index

About

Sisi Zhang is a pioneering researcher at the intersection of intelligent robotics and advanced manufacturing. Her primary contributions lie in robot skill acquisition and additive manufacturing, where she has developed transformative methods for industrial automation. Zhang’s most influential work, “Robot skill acquisition in assembly process using deep reinforcement learning” (2019, 110 citations), introduced a novel framework that enables robots to autonomously learn complex assembly tasks through trial-and-error interaction with their environment. This approach significantly reduces the need for manual programming, accelerating deployment in flexible manufacturing settings. More recently, Zhang has ventured into construction-scale 3D printing with her development of the AMoRC method (2023), an innovative process for printing reinforced concrete structures that promises to revolutionize sustainable building practices. Her research bridges the gap between machine learning and physical fabrication, demonstrating how robots can not only learn but also build. With her work cited across robotics, manufacturing, and civil engineering, Zhang is recognized for advancing both the theory and practice of intelligent automation.