Ali Arishi
Papers
2
Total Citations
32
H-Index
2
About
Ali Arishi is a researcher at the forefront of applying deep learning to solve pressing real-world challenges, with a primary focus on sustainable waste management and intelligent industrial automation. His most impactful work, "Real-Time Household Waste Detection and Classification for Sustainable Recycling: A Deep Learning Approach" (2025, 27 citations), directly addresses the critical issue of inefficient household waste sorting. By developing a real-time detection system, Arishi’s contribution targets the contamination of recyclables, a major barrier to effective recycling that leads to increased landfill waste and resource depletion. This work demonstrates a clear pathway from AI innovation to tangible environmental benefit. In parallel, his research on "Deep-Learning-Based Cyber-Physical System Framework for Real-Time Industrial Operations" (2022, 5 citations) showcases his versatility, proposing an intelligent framework that integrates image processing and deep learning to enhance both production efficiency and human safety in complex industrial tasks. Through these contributions, Arishi establishes himself as a key voice in the intersection of artificial intelligence, sustainability, and cyber-physical systems, offering practical, data-driven solutions for a more efficient and environmentally responsible future.
Research Focus
Key Achievements
Top Papers
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- 2