Md Sabid Hasan

Bangladesh University of Engineering and Technology

Papers

Total Citations

H-Index

About

Md Sabid Hasan is a rising researcher at the intersection of machine learning and agricultural technology, with a primary focus on developing intelligent systems for crop disease detection. His most cited work, "Sugarcane Diseases Identification and Detection via Machine Learning" (2023), has already garnered 11 citations, demonstrating early impact in applying computational methods to solve pressing agricultural challenges. Hasan's research leverages deep learning and computer vision techniques to automate the identification of sugarcane diseases, offering a scalable solution that could significantly reduce crop losses and improve yield for farmers. This work not only showcases his technical proficiency in model development and dataset curation but also highlights his commitment to translating AI innovations into practical, real-world applications. As an emerging scholar, Hasan is establishing himself as a key contributor to precision agriculture, where his findings provide a foundation for future studies in plant pathology diagnostics. His growing citation record reflects the relevance and timeliness of his research, positioning him as a promising voice in the ongoing effort to harness machine learning for sustainable farming practices.