Touficur Rahman

Khulna University of Engineering and Technology

Papers

Total Citations

H-Index

About

Touficur Rahman is a researcher at the forefront of agricultural technology, specializing in deep learning, computer vision, and mobile health applications. His work primarily focuses on enhancing crop management and food security through intelligent systems. Rahman’s most notable contribution is the development of a convolutional neural network (CNN)-based framework for early and accurate classification of rice diseases, integrated with a mobile application for real-time field diagnosis. This innovative approach, detailed in his highly cited 2023 paper (32 citations), addresses the critical challenge of reliable disease detection using RGB image data, directly supporting global food security. Beyond agriculture, Rahman has also advanced healthcare accessibility by designing a machine learning-driven mobile app for early diabetes risk prediction, demonstrating his commitment to applying AI for societal benefit. His research bridges the gap between complex computational models and practical, user-friendly tools, making a tangible impact on both farmers and patients. With a growing citation record and a focus on solving real-world problems, Rahman is establishing himself as a key contributor to applied AI in sustainable agriculture and digital health.