Papers
9
Total Citations
372
H-Index
6
About
Kui Liu is a pioneering researcher at the intersection of advanced manufacturing, robotics, and artificial intelligence, with particular expertise in additive manufacturing, robotic machining, and digital twin technologies. His most celebrated contributions center on the development of multisensor fusion-based digital twin frameworks for robotic laser-directed energy deposition (DED) processes, work that has garnered an impressive 124 citations since 2023 and is transforming how the manufacturing community approaches in-situ quality monitoring and defect correction. By integrating real-time sensor data with predictive modeling, Liu has enabled localized quality prediction and adaptive defect correction during live builds — a significant leap forward in making additive manufacturing more reliable and autonomous. His research extends into robotic stiffness modeling, where he has addressed the nuanced influence of gravity compensators and link weights on industrial robot performance (77 citations), and into surface quality optimization for robotic machining, exploring how process parameters and robot postures interact. Earlier work on magnetic field-assisted finishing further demonstrates the breadth of his manufacturing expertise. Collectively, Liu's research is reshaping intelligent, sensor-driven manufacturing systems and establishing him as a leading voice in smart fabrication and Industry 4.0 innovation.
Research Focus
Key Achievements
Top Papers
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