Shenzhen University | China
Mr. Ibtasam Wajid is an emerging researcher whose work focuses on the intersection of biomedical engineering, health informatics, and data science, with a particular interest in developing innovative machine learning and deep learning models for improving healthcare outcomes. His research explores how advanced computational techniques can be applied to disease prediction, medical imaging, and clinical decision support, contributing to the growing field of digital health transformation. With an academic background spanning biochemistry, health informatics, and biomedical research, he brings an interdisciplinary perspective to addressing complex challenges in modern medicine. He has authored three research documents, accumulating a total of six citations and holding an h-index of one, reflecting a steadily growing research impact at an early stage of his academic career. Alongside his research contributions, he has actively participated in mentoring undergraduate students, organizing technical workshops, and promoting collaborative learning environments within the scientific community. His ongoing studies and projects continue to focus on integrating artificial intelligence into healthcare systems to enhance accuracy, efficiency, and patient-centered care. Through his dedication to continuous learning and innovation, he demonstrates the potential to make lasting contributions to biomedical science and the advancement of data-driven healthcare solutions worldwide.
Profiles: Scopus | Google Scholar
Featured Publications
Sultan, H., Javed, I., Zubair, M., Iqbal, K., Bilal, M., Iqbal, J., & Wajid, I. (2021). Protein and polysaccharide-based biomaterial for the formation of composite bone scaffold. AlQalam Journal of Medical and Applied Sciences, 4(2), 80–88.
Wajid, I., Dan, L., & Wang, Q. (2025). Hybrid ensemble approaches for cardiovascular disease prediction: Leveraging interpretable AI for clinical insight. Intelligence-Based Medicine, 100297.
Ishaq, S., Afzal, S., Usmani, S. A., Wajid, I., Aziz, A., Tahir, R., Ahmad, A., & Ullah, A. (2025). Inflammatory cell death and leukemia treatment. Critical Reviews in Oncology/Hematology, 104909.