Alireza Sharifi
Papers
1
Total Citations
12
H-Index
1
About
Alireza Sharifi is a researcher at the forefront of applying deep learning and robotics to critical challenges in sustainable waste management and recycling. His work centers on developing automated systems for the intelligent sorting and processing of electronic waste, with a particular focus on the complex problem of used button cell batteries. His most cited study, "Robotic Sorting of Used Button Cell Batteries: Utilizing Deep Learning" (2018, 12 citations), introduces a pioneering technique that leverages deep learning to automatically classify batteries by their chemical composition based on surface markings. This contribution is vital for enabling safe, efficient, and scalable recycling of hazardous battery components, directly addressing a pressing environmental and resource recovery need. By integrating computer vision with robotic manipulation, Sharifi’s research demonstrates a practical pathway toward reducing manual labor and improving accuracy in e-waste processing. His work stands as a notable achievement in the intersection of artificial intelligence and environmental engineering, offering a compelling solution for a cleaner, more sustainable future.
Research Focus
Key Achievements
Top Papers
- 1Robotic Sorting of Used Button Cell Batteries: Utilizing Deep Learning12 citations · 2018