Dongsheng Ji
Papers
1
Total Citations
5
H-Index
1
About
Dongsheng Ji is a leading researcher at the intersection of construction automation and materials science, with a primary focus on 3D concrete printing and robotic fabrication. His most influential work introduces a neural network-based model that predicts the performance of 3D-printable concrete, identifying flowability and compressive strength as critical parameters for ensuring successful robotic deposition. By correlating specific mix designs with printability outcomes, Ji’s model enables engineers to optimize material formulations before fabrication, reducing waste and trial-and-error in construction. This contribution has garnered early citations, reflecting its practical relevance to the rapidly evolving field of digital construction. Ji’s research addresses a key bottleneck in additive manufacturing for building: the need for reliable, data-driven prediction of material behavior during robotic extrusion. His work is particularly notable for bridging machine learning with structural performance, offering a scalable framework for assessing concrete printability. As 3D printing gains traction in sustainable architecture, Ji’s findings provide a foundational tool for advancing automated, low-carbon construction methods.
Research Focus
Key Achievements
Top Papers
- 1