Md. Mehedi Hasan

Md. Mehedi Hasan is a Computer Science and Engineering graduate with experience spanning artificial intelligence, machine learning, data science, computer vision, data annotation, and biomedical AI research. His research interests focus primarily on graph neural networks, graph transformers, explainable artificial intelligence, and their applications to healthcare, medical imaging, biomedical data, and bioinformatics. He is particularly interested in developing reliable and interpretable machine learning frameworks for complex structured and real-world datasets. He completed his undergraduate degree in Computer Science and Engineering at the Bangladesh University of Business and Technology, Dhaka, Bangladesh, where he received multiple merit-based tuition fee waivers in recognition of his academic performance. He also served as a Teaching Assistant, supporting undergraduate courses through laboratory instruction, coursework assistance, debugging, grading, academic mentoring, and hands-on technical guidance. Currently, he works as a Data Annotation Analyst at Rooya Bangladesh, contributing to AI and machine learning projects through data annotation, quality validation, dataset preparation, and related data workflows. Previously, he worked as a Research Assistant and Research Intern at the Advanced Machine Intelligence Research Lab, where he contributed to research involving healthcare AI, medical imaging, biomedical data, and graph-based learning. His research experience includes data preprocessing, model development and evaluation, patient-level data validation, class imbalance handling, graph-based modeling, and model interpretability. His technical interests and experience include Python, SQL, data analysis, data annotation, machine learning, deep learning, computer vision, explainable AI, PyTorch, Scikit-learn, Pandas, NumPy, and Git. He is particularly interested in applying machine learning and data-driven methods to challenging problems in healthcare and biomedical domains. Beyond research and professional work, Mehedi is actively involved in IEEE and professional community activities. As a member of IEEE and the IEEE Computer Society, he has contributed to conferences, symposiums, student activities, technical programs, outreach initiatives, and professional development activities. He has held multiple volunteer and organizational leadership roles and has received several competitive recognitions, including the IEEE Computer Society Richard E. Merwin Student Scholarship and multiple Best Student Volunteer awards from the IEEE Computer Society Bangladesh Chapter. He is interested in research and professional opportunities in Artificial Intelligence, Machine Learning, Data Science, Computer Vision, Medical Imaging, Biomedical AI, Explainable AI, Bioinformatics, and related fields. He is also open to MSc and PhD opportunities where he can contribute to impactful, interpretable, and reliable AI research and practical solutions.