Rumana Sultana
Papers
1
Total Citations
35
H-Index
1
About
Rumana Sultana is a researcher at the forefront of applying deep learning to environmental sustainability, with a primary focus on intelligent waste management and smart city technologies. Her most impactful work, "Trash and Recycled Material Identification using Convolutional Neural Networks (CNN)" (2020, 35 citations), addresses a critical urban challenge: automating the detection and classification of trash in public spaces. By developing and comparing two Convolutional Neural Network architectures, Sultana demonstrated how image processing algorithms can significantly improve municipal waste collection systems, moving beyond manual sorting toward efficient, AI-driven solutions. This research not only advances computer vision applications in environmental engineering but also provides a scalable framework for creating cleaner, smarter cities. Her work bridges the gap between deep learning theory and practical urban infrastructure, offering a data-driven approach to recycling and waste management that has attracted attention from both academic and municipal stakeholders. Sultana's contributions exemplify how targeted machine learning applications can solve real-world environmental problems, making her research particularly relevant for students and professionals interested in the intersection of artificial intelligence, sustainability, and urban planning.
Research Focus
Key Achievements
Top Papers
- 1