Awal Ahmed Fime
Southern Illinois University Carbondale, Kent State University
Papers
5
Total Citations
13
H-Index
2
About
Awal Ahmed Fime is a rising researcher at the forefront of integrating artificial intelligence with robotic systems for disaster response. His work centers on enhancing victim detection and multi-robot collaboration in catastrophic environments, leveraging deep learning, large language models (LLMs), and multimodal data fusion. Fime’s most cited paper, “ATR HarmoniSAR” (2024, 7 citations), introduces a system that significantly improves victim detection in robot-assisted disaster scenarios, addressing a critical need for efficient search and rescue. He further advances the field with a novel LLM-based approach for robotic collaboration (2024, 2 citations), enabling more effective communication and object identification during operations. Fime has also contributed a comprehensive survey on automatic scene generation (2025, 2 citations), highlighting its applications in robotics and simulation. His development of the MechLMM framework (2024, 1 citation) showcases a collaborative knowledge system for enhanced data fusion in multi-robot teams, while his work on firefighting robots (2025, 1 citation) extends his impact to practical emergency response. With a growing citation record and a focus on real-world applications, Fime is establishing himself as a key innovator in AI-driven disaster robotics.
Research Focus
Key Achievements
Top Papers
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