Fan Dang

Tsinghua University, Ion Exchange (India)

Papers

Total Citations

H-Index

About

Fan Dang is a pioneering researcher at the intersection of artificial intelligence and cyber-physical systems, with a primary focus on integrating large language models (LLMs) into real-world applications and multi-robot coordination for emergency response. Her most-cited work, "Integration of LLMs and the Physical World: Research and Application" (2024, 5 citations), establishes a foundational framework for deploying LLMs in smart environments, demonstrating how these models can bridge the gap between digital intelligence and physical tasks like smart home automation. This contribution is particularly notable for its forward-looking approach to making AI context-aware and actionable in everyday settings. Dang also addresses critical societal challenges through her work "FireHunter: Toward Proactive and Adaptive Wildfire Suppression via Multi-UAV Collaborative Scheduling" (2024, 2 citations), where she develops a novel multi-drone system capable of dynamically coordinating fire monitoring and suppression in unpredictable, large-scale scenarios. This research showcases her expertise in multi-agent systems and cold-start problem-solving, offering a proactive solution to a pressing environmental crisis. With her innovative blend of LLM integration and robotics, Dang is shaping the future of intelligent, responsive systems that directly impact human safety and daily life.