Hasibul Hasan Rupok
Papers
1
Total Citations
4
H-Index
1
About
Hasibul Hasan Rupok is an emerging researcher at the intersection of artificial intelligence and sustainable technology, with a primary focus on e-waste management, deep learning, and IoT-driven automation. His most notable contribution is the development of **ElectroSortNet**, a novel convolutional neural network (CNN) architecture designed for the automated classification of electronic waste. This work, published in 2024 and already garnering **4 citations**, addresses a critical environmental challenge: the recovery of valuable resources from e-waste, which contains 100 times more gold per tonne than gold ore. By integrating this AI-based classification system with an IoT-enabled separation mechanism, Rupok’s research offers a scalable, intelligent solution for recycling facilities, reducing manual sorting and enhancing material recovery rates. His work stands out for its practical impact, bridging computer vision and environmental engineering to tackle one of the fastest-growing waste streams globally. As a forward-thinking innovator, Rupok is positioning himself at the forefront of green AI, demonstrating how machine learning can directly contribute to a circular economy and sustainable industrial practices.
Research Focus
Key Achievements
Top Papers
- 1