Zannatul Ferdaus Rinku

About

Zannatul Ferdaus Rinku is a researcher at the intersection of computer vision and public health, with a primary focus on leveraging deep learning for vector-borne disease control. Her most cited work, "Detection of Mosquito Larvae Using Convolutional Neural Network" (2021, 5 citations), introduces a novel, proactive approach to mosquito population management. Rather than targeting adult mosquitoes—a strategy that has proven largely ineffective—Rinku’s research proposes using convolutional neural networks to detect mosquito larvae at their source. This early-stage intervention offers a more sustainable and impactful method for reducing the transmission of deadly diseases such as dengue, malaria, and Zika. By shifting the focus from reactive barriers to intelligent, image-based larval surveillance, her work demonstrates a practical application of AI in global health. Though early in her career, Rinku’s contributions highlight the potential of computational methods to address pressing environmental and epidemiological challenges, making her a promising voice in the growing field of AI-driven public health solutions.

Research Focus

Key Achievements

Top Papers

1. 1
   Detection of Mosquito Larvae Using Convolutional Neural Network

   5 citations · 2021

Key Collaborators

Contact & Links