Ali Ghulam | AI in Healthcare | Best Researcher Award

Dr. Ali Ghulam | AI in Healthcare | Best Researcher Award

Assistant Professor at Information Technology Centre, Sindh Agriculture University, Pakistan

Dr. Ghulam Ali is an accomplished academic and researcher specializing in artificial intelligence (AI) and bioinformatics. He earned his Ph.D. in Computer Software and Theory from Shaanxi Normal University, Xi’an, China, in 2020. Currently, he serves as an Assistant Professor at the Information Technology Centre, Sindh Agriculture University, Tandojam. His research focuses on human disease pathway network modeling, biological pathway database discovery, and AI-driven predictions related to proteins, drugs, and diseases. With over 20 published SCI articles in high-impact journals and extensive contributions to machine learning applications in bioinformatics, Dr. Ali is a recognized expert in his field.

Profile

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Education

Dr. Ali pursued his Ph.D. from Shaanxi Normal University, Xi’an, China, specializing in bioinformatics and AI. His thesis, titled “Prediction of Pathway Related Protein, Drug and Disease Association Based on Complex Network and Deep Learning,” was supervised by Prof. Xiujuan Lei. He completed his M.Phil. in Computer Science with a specialization in Search Engine Optimization from the University of Sindh, Jamshoro. His academic journey began with a Bachelor of Computer Science (BCS-Hons) from the same university. Additionally, he obtained various certifications and diplomas in information technology, further strengthening his expertise in computing and AI.

Experience

Dr. Ali has a strong academic and research background, currently holding the position of Assistant Professor at Sindh Agriculture University, Tandojam. His professional journey includes extensive work on bioinformatics, AI-based predictive models, and computational biology. He has contributed significantly to research in AI applications for human protein sequence analysis, disease detection, and biomedical data transformation. With a deep understanding of AI, deep learning, and machine learning techniques, he has played a pivotal role in advancing bioinformatics research and education.

Research Interests

Dr. Ali’s research primarily revolves around bioinformatics and artificial intelligence. He is particularly focused on human disease pathway modeling, drug-protein interaction prediction, and machine learning applications in genomics. His work involves utilizing AI to enhance precision diagnostics, early-stage disease detection, and advanced biomedical data analysis. By leveraging deep learning and AI-driven methodologies, Dr. Ali aims to improve healthcare analytics and disease treatment strategies. His research has practical implications in the fields of computational biology, digital health frameworks, and AI-driven medical solutions.

Awards and Recognitions

Dr. Ali has received numerous accolades for his contributions to AI and bioinformatics research. His high-impact factor publications and citations reflect his significant contributions to the scientific community. With an H-index of 12 on Google Scholar, an i10-index of 18, and a ResearchGate H-index of 11, his research has been widely recognized and cited. He has also been nominated for various research excellence awards, highlighting his influence in the field of computational biology and AI-driven biomedical advancements.

Publications

Ali, Ghulam, et al. (2025). “StackAHTPs: An explainable antihypertensive peptides identifier based on heterogeneous features and stacked learning approach.” IET Systems Biology, 19(1), e70002. (SCI, IF: 1.9, Cited by: X).

Arif, Muhammad, et al. (2024). “StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features.” Methods, 230, 129-139. (SCI, IF: 4.02, Cited by: X).

Arif, Muhammad, et al. (2024). “DPI_CDF: Druggable protein identifier using cascade deep forest.” BMC Bioinformatics, 25(1), 1-18. (SCI, IF: 3.09, Cited by: X).

Talpur, Fauzia, et al. (2024). “ML-Based Detection of DDoS Attacks Using Evolutionary Algorithms Optimization.” Sensors, 24(5), 1672. (SCI, IF: 3.09, Cited by: X).

Ghulam, Ali, et al. (2024). “Assessment of Performance of Machine Learning Classification Techniques for Monkey Pox Disease Detection.” Journal of Innovative Intelligent Computing and Emerging Technologies, 1(1), 1-7. (Cited by: X).

Memon, Mukhtiar, et al. (2023). “AiDHealth: An AI-enabled Digital Health Framework for Connected Health and Personal Health Monitoring.” (Cited by: X).

Sikander, Rahu, et al. (2023). “Identification of cancerlectin proteins using hyperparameter optimization in deep learning and DDE profiles.” Mehran University Research Journal of Engineering & Technology, 42(4), 28-40. (WoS, Cited by: X).

Conclusion

Dr. Ghulam Ali is a distinguished researcher and academician in the field of artificial intelligence and bioinformatics. His contributions to AI-driven biomedical research, particularly in disease pathway modeling and predictive analytics, have significantly advanced the field. With a strong publication record, multiple citations, and a commitment to innovation, he continues to influence computational biology and digital health research. His work bridges the gap between AI and medical sciences, paving the way for future breakthroughs in bioinformatics and AI-driven healthcare solutions.

Haleh Ayatollahi | AI in Healthcare | Best Researcher Award

Dr. Haleh Ayatollahi | AI in Healthcare | Best Researcher Award

Faculty member | Iran University of Medical Sciences | Iran

Dr. Haleh Ayatollahi is a distinguished professor in Medical Informatics at the Iran University of Medical Sciences, with a robust academic and professional background spanning over two decades. Her research and professional endeavors focus on leveraging health information technology to address global healthcare challenges, particularly in the areas of telemedicine, health data management, and disease-specific interventions. With a career encompassing significant leadership roles, extensive teaching experience, and a prolific research portfolio, Dr. Ayatollahi has emerged as a leading figure in health informatics, contributing significantly to evidence-based healthcare policies and innovative digital solutions.

Profile

Scopus

Education

Dr. Ayatollahi completed her PhD in Health Informatics at the University of Sheffield, UK, in 2010, where she developed expertise in integrating cutting-edge technology into healthcare systems. She previously obtained her M.Sc. in Medical Records Education (2002) and B.Sc. in Medical Records (1998) from the Iran University of Medical Sciences, solidifying her foundation in health information management. Her academic journey began with an Associate Degree in Medical Records in 1996, also at the same institution. These accomplishments have provided her with a multidimensional perspective on healthcare data management and informatics.

Professional Experience

Dr. Ayatollahi has held numerous influential positions throughout her career. Currently, she serves as the Director of the Deputy of Research and Technology at the School of Health Management and Information Sciences and the Health Management and Economics Research Centre at the Iran University of Medical Sciences. Additionally, she is a member of the Medical Informatics Evaluation and Examination Board. Her leadership roles also include her tenure as the Postgraduate and Education Office Administrator (2014–2016). With early career experiences as a lecturer and teaching assistant, Dr. Ayatollahi has been instrumental in mentoring future professionals in health informatics and medical records.

Research Interests

Dr. Ayatollahi’s research interests include the application of telemedicine technologies, health information systems, and data quality assessment in healthcare. She is deeply committed to advancing the use of digital tools for patient care, particularly in chronic disease management, pediatric healthcare, and emergency medical services. Her studies often emphasize the importance of user-centered approaches, policy development, and technological integration in resource-limited settings, contributing to both the theoretical and practical aspects of health informatics.

Awards and Recognitions

Dr. Ayatollahi has been recognized for her contributions to health informatics and education through several prestigious awards and nominations. Her work has been pivotal in shaping health information technology policies, for which she has earned acknowledgment from academic and professional bodies. These accolades reflect her dedication to excellence in research, teaching, and leadership.

Selected Publications

Global, regional, and national stillbirths at 20 weeks’ gestation or longer in 204 countries and territories, 1990–2021. The Lancet, 2024; cited by 22 articles.

A fuzzy ontology-based case-based reasoning system for stomach dystemperament in Persian medicine. PLOS ONE, 2024; cited by 5 articles.

Acceptance and use of mobile health technology in post-abortion care. BMC Health Services Research, 2024; cited by 8 articles.

Challenges of using telemedicine for patients with diabetes during the COVID-19 pandemic. Journal of Clinical & Translational Endocrinology, 2024; cited by 10 articles.

Application of telemedicine technology for cardiovascular diseases management during the COVID-19 pandemic. Frontiers in Cardiovascular Medicine, 2024; cited by 6 articles.

Machine Learning Techniques for Predicting Drug-Related Side Effects. Pharmaceuticals, 2024; cited by 3 articles.

Motivating and inhibiting factors influencing the application of mHealth technology in post-abortion care: A review study. BMC Pregnancy and Childbirth, 2024; cited by 4 articles.

Conclusion

Dr. Haleh Ayatollahi’s extensive contributions to medical informatics are a testament to her dedication to improving healthcare delivery and outcomes through innovative technology. Her work in health information systems, telemedicine, and education continues to influence both national and global healthcare policies. As a leader, educator, and researcher, Dr. Ayatollahi remains committed to advancing the field of health informatics and empowering the next generation of healthcare professionals.