Ali Ghulam | AI in Healthcare | Best Researcher Award

Posted on by sciencefather

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

Orcid

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.

Abu Sarwar Zamani | AI in Healthcare | Best Researcher Award

Posted on by sciencefather

Dr. Abu Sarwar Zamani | AI in Healthcare | Best Researcher Award 

Asst. Professor | Prince Sattam bin Abdulaziz University | Saudi Arabia

Dr. Abu Sarwar Zamani is a dedicated and disciplined academic and research professional with over 15 years of experience. Specializing in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning, Data Mining, and the Internet of Things (IoT), he has made significant contributions in both the academic and research fields. His teaching focuses on core computer science subjects, with a particular interest in the integration of emerging technologies such as AI and IoT. His professional journey reflects a passion for knowledge sharing and innovative research, contributing to scientific advancements in computer science and technology. Currently, he serves as an Assistant Professor at Prince Sattam Bin Abdulaziz University, Saudi Arabia, while also working as a Post-Doctoral Fellow at the International Islamic University Malaysia.

Profile

Scholar

Education

Dr. Zamani’s academic foundation includes a Ph.D. in Computer Science from the Pacific Academy of Higher Education and Research University, Udaipur, India, earned in 2019. Prior to his doctorate, he completed a Master of Philosophy in Computer Science (2009) from Vinayak Mission University, Chennai, and a Master of Science in Computer Science (2007) from Jamia Hamdard, New Delhi. His undergraduate studies were in Computer Applications at MCRP, Bhopal, India (2002). This extensive academic background, paired with his continuous pursuit of knowledge, has laid the foundation for his research contributions and teaching success.

Experience

Dr. Zamani has held various academic positions throughout his career. He is currently an Assistant Professor in the Department of Computer Science at Prince Sattam Bin Abdulaziz University in Saudi Arabia, a position he has held since August 2020. In addition to his teaching role, Dr. Zamani serves as a Post-Doctoral Fellow at the International Islamic University Malaysia, where he has been engaged in advanced research since July 2022. Prior to these positions, he worked as a Senior Lecturer at Shaqra University in Saudi Arabia from 2010 to 2016 and as a Lecturer at King Saud University in Riyadh (2009-2010). His academic career began as a Lecturer at Ibne Seena Pharmacy College in India (2007-2009). Over the years, Dr. Zamani has contributed significantly to both the academic and administrative frameworks of these institutions, including curriculum development and research committees.

Research Interests

Dr. Zamani’s research interests lie primarily in AI, ML, Deep Learning, Data Mining, IoT, and their applications in various domains. His work focuses on leveraging machine learning techniques to develop predictive models for healthcare, cybersecurity, and educational services. He has also researched IoT-based systems, contributing to advancements in real-time data analytics for improved decision-making and optimization of resources. His research has garnered attention in areas like automated disease detection, smart health monitoring, and the design of secure and efficient systems for IoT networks.

Awards

Dr. Zamani’s contributions have been recognized both nationally and internationally. He has been granted three international patents from India and Australia, further solidifying his standing as an innovator in the fields of machine learning and IoT-based systems. His patents cover key areas such as machine learning-based prediction systems for heart disease and systems for improving educational services. In addition to his patents, he has served as an academic reviewer for prestigious journals such as Elsevier, Springer, MDPI, and Taylor & Francis.

Publications

Dr. Zamani has published more than 100 papers in SCI, PubMed, and Scopus-indexed journals, as well as two conference papers. Some of his significant publications include:

Zamani, A. S., et al. “Implementation of machine learning techniques with big data and IoT to create effective prediction models for health informatics.” Biomedical Signal Processing and Control, 2024, Elsevier, DOI: 10.1016/j.bspc.2024.106247.

Zamani, A. S., et al. “The Prediction of Sleep Quality using Wearable-assisted Smart Health Monitoring System based on Statistical Data.” Journal of King Saud University-Science, 2023, Elsevier, DOI: 10.1016/j.jksus.2023.102927.

Zamani, A. S., et al. “Machine Learning Techniques for Automated and Early Detection of Brain Tumor.” International Journal of Next-Generation Computing, 2022, Perpetual Innovation, DOI: 10.47164/ijngc.v13i3.711.

Zamani, A. S., et al. “Cloud Network Design and Requirements for the Virtualization System for IoT Networks.” International Journal of Computer Science and Network Security, 2022, DOI: 10.22937/IJCSNS.2022.22.11.101.

Zamani, A. S., et al. “Towards Applicability of Information Communication Technologies in Automated Disease Detection.” International Journal of Next-Generation Computing, 2022, Perpetual Innovation, DOI: 10.47164/ijngc.v13i3.705.

Akhtar, M. M., Zamani, A. S., et al. “Stock Market Prediction Based on Statistical Data Using Machine Learning Algorithm.” Journal of King Saud University-Science, 2022, Elsevier, DOI: 10.1016/j.jksus.2022.101940.

Prasad, V. D. P., Zamani, A. S., et al. “Computational Technique Based on Machine Learning and Image Processing for Medical Image Analysis of Breast Cancer Diagnosis.” Security and Communication Networks, 2022, Hindawi, DOI: 10.1155/2022/1918379.

Conclusion

Dr. Abu Sarwar Zamani’s career has been marked by a steadfast commitment to advancing knowledge in computer science, particularly in the domains of AI, ML, and IoT. His extensive experience in both teaching and research has made him a key figure in these fields, with numerous published works and patents to his name. As a dedicated educator and researcher, Dr. Zamani continues to make valuable contributions to the academic community and industry, with a focus on developing innovative solutions for healthcare, cybersecurity, and education. His work exemplifies the intersection of technology and human well-being, ensuring that his research has a lasting impact on society.