Nisreen Innab
Papers
4
Total Citations
28
H-Index
2
About
Dr. Nisreen Innab is a rising researcher at the forefront of intelligent robotics and autonomous systems, with a particular focus on integrating artificial intelligence into real-world navigation and decision-making. Her work primarily spans three interconnected domains: agricultural robotics, multi-robot coordination, and autonomous driving. Dr. Innab’s most impactful contribution is her 2023 study, which introduced an enhanced fuzzy MADM approach for assessing field robots in agriculture—a work that has already garnered 17 citations for its practical framework in evaluating robotic performance. She is also pioneering the use of deep reinforcement learning for collision avoidance in unknown environments, a 2025 paper that addresses critical gaps in motion planning by enabling robots to learn adaptive navigation strategies through action-reward principles. Further demonstrating her versatility, Dr. Innab has developed hybrid bio-inspired neural networks for real-time evasion in dynamic multi-robot systems and proposed a lifelong reinforcement learning approach for self-driving cars operating in partially observable environments. Her research is notable for bridging theoretical AI advances with tangible robotic applications, making her a promising voice in the quest for more autonomous, resilient, and intelligent machines.
Research Focus
Key Achievements
Top Papers
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