Hai-peng Shi
Papers
1
Total Citations
5
H-Index
1
About
Hai-peng Shi is a rising researcher at the intersection of artificial intelligence and engineering project management. His work focuses on leveraging generative AI and large language models (LLMs) to automate complex engineering workflows. Shi’s most notable contribution is the development of an automated task planning system that integrates validated robotic instructions, deep learning models, and demonstration cases within a Work Breakdown Structure (WBS) framework—a standard tool in engineering project management. This innovative approach, detailed in his 2024 paper "LLM-Project: Automated Engineering Task Planning via Generative AI and WBS Integration," has already garnered 5 citations, signaling growing interest in his methodology. By bridging the gap between AI-driven automation and traditional project planning, Shi is pioneering more efficient, scalable solutions for engineering task decomposition and execution. His work holds promise for reducing human error and accelerating project timelines in fields ranging from robotics to construction. As an emerging voice in AI-assisted engineering, Shi’s research is poised to influence both academic inquiry and industrial practice, making him a researcher to watch in the evolving landscape of intelligent automation.
Research Focus
Key Achievements
Top Papers
- 1