Akram Azad | AI in Healthcare | Best Researcher Award

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Prof. Dr. Akram Azad | AI in Healthcare | Best Researcher Award

Professor at Iran University of Medical Sciences (IUMS), Iran

Dr. Akram Azad is a distinguished academic and professional in the field of Occupational Therapy, serving as a Professor at the Rehabilitation Research Center, Department of Occupational Therapy, School of Rehabilitation Sciences, Iran University of Medical Sciences (IUMS), Tehran, Iran. With over three decades of dedicated service in education, research, and clinical rehabilitation, Dr. Azad has significantly contributed to the advancement of rehabilitation sciences in Iran and internationally. Her extensive background in developing rehabilitation tools and expertise in physical dysfunctions, especially in upper extremity disorders, stroke, and geriatric rehabilitation, has positioned her as a thought leader in the occupational therapy domain. With a strong academic portfolio and a passion for mentorship, she has supervised numerous undergraduate, postgraduate, and doctoral students, nurturing the next generation of therapists and researchers.

Profile

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Education

Dr. Azad’s academic journey is deeply rooted in the Iran University of Medical Sciences, where she completed all her higher education. She earned her Ph.D. in Occupational Therapy from the School of Rehabilitation at IUMS between 2010 and 2014, focusing on evidence-based practices in therapeutic interventions. Earlier, she pursued her MSc in Occupational Therapy with a specialization in physical dysfunctions from the same institution from 1993 to 1996, laying a strong clinical foundation for her later academic pursuits. Her professional career began with a B.Sc. in Occupational Therapy, earned between 1983 and 1987, which marked the beginning of her long-standing commitment to patient care and rehabilitation sciences.

Experience

Dr. Azad has amassed extensive experience in various areas of rehabilitation. Her clinical expertise includes the development and validation of rehabilitation tools, with a special emphasis on therapeutic interventions for upper extremity problems, stroke rehabilitation, and musculoskeletal disorders in children. A key area of her focus has also been geriatric rehabilitation, where she has addressed the unique challenges faced by the aging population. Her multidisciplinary approach combines clinical practice with empirical research to innovate and refine therapeutic methodologies, particularly for populations with complex rehabilitation needs.

Research Interest

Her research interests are closely aligned with her clinical focus and include the development of standardized assessment tools, rehabilitation methodologies for upper limb impairments, stroke recovery strategies, and functional improvement among older adults. Additionally, she has explored pediatric musculoskeletal issues, advancing the understanding and treatment of childhood disabilities. Dr. Azad is also deeply invested in knowledge dissemination through systematic literature reviews and research methodologies, which she actively teaches and incorporates in her supervision of theses and dissertations.

Award

Throughout her career, Dr. Azad has been recognized for her exceptional contributions to occupational therapy and rehabilitation sciences. She has received several institutional awards and nominations for excellence in research and academic leadership. Her work has significantly influenced policy and practice in rehabilitation in Iran. As a nominee for distinguished academic awards, her dedication to improving the quality of life for patients through innovative rehabilitation approaches has been widely acknowledged in academic and clinical circles.

Publication

Dr. Azad has published approximately 80 articles in English and an additional 25 in Persian, contributing substantially to the literature in occupational therapy. Some of her recent and notable publications include:

Development and validation of a rehabilitation tool for post-stroke upper limb function (2020, Journal of NeuroEngineering and Rehabilitation) – cited by 45 articles.

The efficacy of task-specific training in older adults with upper limb dysfunction (2019, Archives of Gerontology and Geriatrics) – cited by 38 articles.

Reliability and validity of occupational performance tools in Iranian elderly (2018, Disability and Rehabilitation) – cited by 30 articles.

A systematic review of rehabilitation interventions in pediatric musculoskeletal disorders (2021, BMC Pediatrics) – cited by 28 articles.

Comparative analysis of occupational therapy approaches in stroke recovery (2017, Clinical Rehabilitation) – cited by 50 articles.

Design and testing of culturally adapted assessment tools in OT practice (2022, International Journal of Therapy and Rehabilitation) – cited by 15 articles.

Integrative rehabilitation for chronic musculoskeletal conditions: A pilot study (2016, Physiotherapy Research International) – cited by 20 articles.

Conclusion

Dr. Akram Azad’s career stands as a testament to her unwavering dedication to occupational therapy, research, and education. She has not only contributed to academic literature and clinical advancement but has also played a pivotal role in shaping the curriculum and mentoring future professionals in the field. Her work reflects a seamless blend of theory and practice, with a commitment to evidence-based rehabilitation that has impacted countless lives. With her broad spectrum of expertise and scholarly output, Dr. Azad continues to be a prominent figure in rehabilitation sciences, inspiring innovation and excellence in occupational therapy both in Iran and beyond.

Ali Ghulam | AI in Healthcare | Best Researcher Award

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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.