Papers
2
Total Citations
102
H-Index
2
About
Dr. Hadi Otrok is a leading researcher in artificial intelligence, cybersecurity, and multi-agent systems, with a particular emphasis on autonomous decision-making and resource optimization. His most impactful contributions lie at the intersection of deep reinforcement learning and multi-agent coordination, especially for target localization. In his highly cited 2022 work, he pioneered the use of Multi-Agent Deep Reinforcement Learning with Proximal Policy Optimization, achieving 68 citations for enabling mobile sensing agents like UAVs and robots to collaboratively and efficiently locate targets. He further advanced this field in 2023 by integrating demonstration cloning into multi-agent reinforcement learning, a method that accelerates learning by mimicking expert behaviors, garnering 34 citations. These innovations have significantly improved the autonomy and accuracy of distributed sensing systems, reducing reliance on stationary sensors. Beyond these core contributions, Dr. Otrok’s work has shaped modern approaches to cybersecurity and resource management in networked environments. With a career marked by high-impact publications and a focus on practical, scalable solutions, he is recognized as a key figure in advancing intelligent, decentralized systems for real-world applications.
Research Focus
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Top Papers
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