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About

Prashnna Ghimire is an emerging researcher at the intersection of robotics, artificial intelligence, and construction technology, with a focus on advancing automation in built environment applications. His work explores how intelligent systems can be deployed in complex, real-world settings such as power plant facilities and construction sites, addressing practical challenges that have long resisted automation. Ghimire's most notable contributions center on integrating large language models (LLMs) with construction robotics to enable more flexible and intuitive task planning. His framework for LLM-enabled robot task planning — applied to interior wall painting — demonstrates how natural language communication between robots and AI systems can replace rigid, conventional programming approaches, lowering barriers to robotic deployment on job sites. This work, alongside his research on context-aware and adaptive task planning through LLM-robot communication, has garnered early citation recognition within a competitive field. His earlier work examining robotics applicability for routine operator tasks in power plant facilities further reflects a broad commitment to reducing human exposure to hazardous or repetitive environments. Collectively, Ghimire's research signals a productive trajectory toward smarter, more adaptable construction and industrial robots — a contribution increasingly relevant as the industry confronts persistent labor shortages and safety challenges.