Giriraj Mannayee
Papers
2
Total Citations
8
H-Index
2
About
Giriraj Mannayee is at the forefront of applying artificial intelligence to solve pressing real-world challenges, with a dual focus on environmental sustainability and autonomous robotics. His pioneering work in waste management, detailed in his 2024 paper "An Evaluation of Various Deep Convolutional Networks for the Development of a Vision System for the Classification of Domestic Solid Street Waste," demonstrates how deep learning can revolutionize urban sanitation by enabling automated, accurate sorting of household refuse. Complementing this environmental contribution, Mannayee has made significant strides in mobile robotics through his research on "Dynamic Path Planning Algorithm for Mobile Robots: Leveraging Reinforcement Learning for Efficient Navigation." This work introduces a novel Markov Decision Process-based algorithm that empowers robots to intelligently navigate unfamiliar and complex terrains. Both papers have rapidly garnered attention, each accumulating 4 citations shortly after publication, signaling their immediate relevance to the AI and robotics communities. Mannayee’s research stands out for its direct applicability—bridging cutting-edge machine learning techniques with tangible solutions for smart cities and autonomous systems, marking him as an emerging innovator in applied artificial intelligence.
Research Focus
Key Achievements
Top Papers
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- 2