Haleh Ayatollahi | Public Health Informatics | Research Excellence Award

Dr. Haleh Ayatollahi | Public Health Informatics | Research Excellence Award

Iran University of Medical Sciences | Iran

Haleh Ayatollahi is a Professor of Medical Informatics with extensive experience in health information management, digital health, and health technology assessment. She holds a PhD in Health Informatics from the University of Sheffield (UK), an MSc and BSc in Medical Records from Iran University of Medical Sciences, and an associate degree in the same field. She has held several senior academic and executive roles, including Director of the Deputy of Research and Technology at both the School of Health Management and Information Sciences and the Health Management and Economics Research Centre, and membership on the Medical Informatics Evaluation and Examination Board. Her academic career spans teaching, research leadership, postgraduate administration, and international collaboration. Her research focuses on telemedicine, mobile health, clinical decision support systems, artificial intelligence in healthcare, digital health evaluation, health information systems, patient safety, and technology adoption, with strong contributions to policy briefs and global health studies, including the Global Burden of Disease projects. She has authored 108 peer-reviewed documents with 6,293 citations across 5,499 citing documents and an h-index of 21, reflecting sustained scholarly impact. She has contributed to high-impact journals such as The Lancet, BMC series, Digital Health, and PLOS ONE, and has received multiple academic and research recognitions for excellence in education, research productivity, and leadership in medical informatics.

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Featured Publications


Clinicians’ Knowledge and Perception of Telemedicine Technology

Perspectives in Health Information Management, 2015

Umme Habiba | Machine Learning and AI Applications | Research Excellence Award

Mrs. Umme Habiba | Machine Learning and AI Applications | Research Excellence Award

North Dakota State University(NDSU) | United States

Umme Habiba is a dedicated researcher and educator in computer science whose work centers on machine learning, deep learning, transformer-based architectures, explainable AI, and swarm intelligence, particularly within medical data analysis. She is pursuing her Ph.D. and M.Sc. in Computer Science at North Dakota State University, where she has gained extensive teaching experience as an instructor of record and graduate teaching assistant across several undergraduate courses. Her research contributions span clinical text mining, medical risk prediction, brain–computer interface modeling, IoT security, and usability analysis of mHealth applications, with publications in reputable international journals. She has also collaborated on projects involving mobile sensor–based spatial analysis, voice-controlled IoT automation systems, and hybrid ML models for network intrusion detection. Her academic journey began with a bachelor’s degree in Computer Science and Engineering, where she developed a strong foundation in data-driven system design and intelligent applications. She has received consistently high teaching evaluations and has demonstrated a commitment to interdisciplinary research and student learning. Her long-term goal is to contribute impactful solutions at the intersection of artificial intelligence and healthcare while advancing as both a researcher and an educator.

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Featured Publication

PSO-optimized TabTransformer architecture with feature engineering for enhanced cervical cancer risk prediction, 2026