Aowabin Rahman
Papers
2
Total Citations
9
H-Index
2
About
Aowabin Rahman is an emerging researcher specializing in autonomous multi-agent systems, reinforcement learning, and risk-aware robotics, with a focused application to search and rescue (SAR) missions in complex and dynamic environments. His work addresses one of the most challenging frontiers in autonomous systems: coordinating multi-robot teams that must simultaneously manage local control actions, group behaviors, and global mission objectives under uncertain and adversarial conditions. Rahman's 2022 paper, "AdverSAR: Adversarial Search and Rescue via Multi-Agent Reinforcement Learning," has garnered 7 citations and introduced a framework for deploying adversarially robust multi-agent systems in remote SAR scenarios, advancing how autonomous robots handle hostile or unpredictable interference. Building on this foundation, his 2025 work on risk-aware autonomous SAR with multiagent reinforcement learning extends these ideas to high-consequence environments where agents must adapt to evolving adversarial risks in real time. Together, these contributions position Rahman as a thoughtful innovator bridging theoretical reinforcement learning with safety-critical real-world applications. His research holds meaningful implications for disaster response, military operations, and the broader deployment of resilient autonomous systems in unstructured environments.
Research Focus
Key Achievements
Top Papers
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- 2