Israt Jahan Payel | Artificial Intelligence | Best Researcher Award Posted on 09/01/202509/01/2025 by sciencefatherLeave a Comment on Israt Jahan Payel | Artificial Intelligence | Best Researcher Award Ms. Israt Jahan Payel | Artificial Intelligence | Best Researcher Award Ms. Israt Jahan Payel , Daffodil International University, Bangladesh. Ms. Israt Jahan Payel is a dedicated researcher specializing in Artificial Intelligence, machine learning, and healthcare applications. She has developed groundbreaking solutions such as the “Grape Guard” mobile app for grape leaf disease detection, achieving remarkable precision and accuracy. Her innovative work includes a novel Graph Neural Network approach for breast cancer diagnosis and the integration of federated learning with explainable AI for privacy-preserving healthcare. With multiple publications in high-impact journals, including the Journal of Cancer Research and Clinical Oncology, and significant contributions to medical image classification, Payel exemplifies excellence in advancing AI-driven healthcare innovations Professional Profile: Google Scholar Suitability for Best Researcher Award Ms. Israt Jahan Payel is a highly accomplished researcher specializing in Artificial Intelligence, machine learning, and healthcare applications. With a proven track record in groundbreaking research, she has developed innovative solutions such as the YOLOv8-based mobile app “Grape Guard” for grape leaf disease detection, achieving remarkable precision and recall rates. Her work has been published in high-impact journals like the Journal of Cancer Research and Clinical Oncology, and she has proposed novel approaches for breast cancer diagnosis using Graph Neural Networks and federated learning for privacy-preserving healthcare. Israt’s extensive experience as a Research Associate at both the Health Information Research Lab (HIRL) and 4IR Research Cell at Daffodil International University demonstrates her commitment to advancing research in healthcare and AI. Her research and publication list highlight her deep expertise and innovative approach, making her an exceptional candidate for the Best Researcher Award. Education Background: Ms. Israt Jahan Payel has an exemplary academic background in Computer Science and Engineering. She is currently pursuing her Master’s degree at Daffodil International University (DIU), Dhaka, Bangladesh, with a stellar CGPA of 4.00. She completed her Bachelor’s degree in the same discipline from DIU in 2023, achieving an impressive CGPA of 3.87. Payel also excelled in her earlier education, securing a CGPA of 4.42 in her Higher Secondary Certificate (HSC) from Savar Model College, Dhaka, and a perfect CGPA of 5.00 in her Secondary School Certificate (SSC) from ACED School, Dhaka. Her academic journey reflects dedication and excellence. Professional Experience: Ms. Israt Jahan Payel has been actively engaged in research as a Research Associate at the Health Information Research Lab (HIRL) and the 4IR Research Cell at Daffodil International University since 2022. Her work focuses on artificial intelligence, machine learning, and healthcare applications. She has led impactful projects, including developing mobile applications and machine learning models for disease detection and diagnosis. Payel’s expertise spans medical image classification, federated learning, and graph neural networks. Her hands-on experience in research and innovation highlights her ability to address real-world challenges and contribute significantly to advancements in AI and healthcare technologies. 🌍Research Contributions On Artificial Intelligence Ms. Israt Jahan Payel has made significant contributions to artificial intelligence and healthcare research. Her innovative projects include developing the “Grape Guard” app for grape leaf disease detection, achieving exceptional precision and accuracy. She proposed a Graph Neural Network approach for breast cancer diagnosis and integrated federated learning with explainable AI for privacy-preserving healthcare solutions. Her work on multi-modality medical image classification combines X-ray, MRI, and CT modalities for advanced disease detection. With publications in high-impact journals and ongoing research in deep learning, medical imaging, and data analytics, Payel’s contributions address critical healthcare challenges with real-world impact. Award and Recognition Ms. Israt Jahan Payel has been widely recognized for her outstanding contributions to artificial intelligence and healthcare applications. Her innovative project, “Grape Guard,” earned acclaim for achieving exceptional precision in grape leaf disease detection. She has published in high-impact journals such as the Journal of Cancer Research and Clinical Oncology, reflecting her excellence in academic research. Her work on Graph Neural Networks for breast cancer diagnosis and federated learning in healthcare has set benchmarks in the field. A consistent achiever, Payel has been honored for her research excellence and dedication to advancing AI-driven solutions for real-world problems. Publication Top Notes Graph Neural Network-Based Breast Cancer Diagnosis Using Ultrasound Images with Optimized Graph Construction Integrating the Medically Significant Features 📖 Journal of Cancer Research and Clinical Oncology 📅 2023 | 👥 Cited by: 3 DVS: Blood Cancer Detection Using Novel CNN-Based Ensemble Approach 📄 arXiv preprint arXiv:2410.05272 📅 2024 | 👥 Cited by: 1 Grape Guard: A YOLO-Based Mobile Application for Detecting Grape Leaf Diseases 📜 Journal of Electronic Science and Technology 📅 2025 | ✨ New Publication A Low Complexity Efficient Deep Learning Model for Automated Retinal Disease Diagnosis 📚 Journal of Healthcare Informatics Research 📅 2024