Sunawar Khan | Computer Science | Research Excellence Award

Mr. Sunawar Khan | Computer Science | Research Excellence Award

National College of Business Administration | Pakistan

Sunawar Khan is a research-oriented academic and practitioner with strong expertise in artificial intelligence, machine learning, deep learning, cybersecurity, smart grid technologies, Computer Science and intelligent systems. His research interests center on applying advanced computational intelligence techniques to real-world problems, particularly in healthcare analytics, intrusion detection systems, software reliability, and smart city security. He has worked extensively with neural networks, ensemble learning, explainable AI, and hybrid deep learning architectures such as CNN- and BiGRU-based models. His projects include deep learning–based disease detection using benchmark medical datasets, facial expression recognition with neural AdaBoost methods, and software defect prediction using industrial datasets. In cybersecurity, his research focuses on robust intrusion detection for smart environments, emphasizing accuracy, scalability, and interpretability. He also has experience designing and implementing intelligent management systems and applying machine learning to large, structured datasets. His academic background reflects a strong foundation in artificial intelligence, image processing, computer vision, data mining, algorithm analysis, and computational theory, complemented by practical experience in programming and system development. Overall, his research profile demonstrates a commitment to innovative, data-driven solutions that bridge theoretical models and applied intelligent technologies across interdisciplinary domains.

Citation Metrics (Google Scholar)

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Featured Publications


Antenna Systems for IoT Applications: A Review


Discover Sustainability, Vol. 5(1), Article 412, 2024

Generative AI, IoT, and Blockchain in Healthcare: Applications, Issues, and Solutions


Discover Internet of Things, Vol. 5(1), Article 5, 2025

Gang Yang | Statistical Genetics and Genomics | Best Researcher Award

Prof. Gang Yang | Statistical Genetics and Genomics | Best Researcher Award

The First Hospital of Lanzhou University | China

Prof. Gang Yang is a distinguished Professor based in China, currently affiliated with The First Hospital of Lanzhou University, with a major research focus on cerebrovascular disease and glioma. Over his academic career, he has made sustained contributions to understanding molecular mechanisms and clinical implications in neurovascular and neuro-oncology fields. His representative works include: “HNF1A induces glioblastoma by upregulating EPS8 and activating PI3K/AKT signaling pathway” published in Biochemical Pharmacology, “EPS8 is a Potential Oncogene in Glioblastoma” in OncoTargets and Therapy, “Identifying the role of aging-related genes in intracranial aneurysms through bioinformatics analysis” in Chinese Neurosurgical Journal, “Revisiting sinking skin flap syndrome: a series of case reports and literature review on cranioplasty with PEEK implants” in Neurological Research, and “Ferroptosis in early brain injury after subarachnoid hemorrhage: review of literature” in Chinese Neurosurgical Journal. His body of work interweaves molecular biology, signaling pathways, bioinformatics, and translational neurosurgical topics, with a particular emphasis on how genes such as EPS8 drive glioblastoma progression and how neurovascular injury processes involve oxidative stress and ferroptotic pathways. He is also active in reporting clinical neurosurgical phenomena such as sinking skin flap syndrome and exploring genetic and aging mechanisms underlying aneurysm development, reflecting his dual interest in both basic and clinical neuroscience. Professor Yang’s academic record demonstrates a profound commitment to bridging laboratory findings with clinical applications, enhancing diagnosis, and therapeutic strategies for brain tumors and cerebrovascular conditions. He has authored 8 peer-reviewed publications, which have collectively received 63 citations, resulting in an h-index of 4. His expertise in molecular oncology, vascular neurosurgery, and bioinformatics establishes him as a leading figure in cerebrovascular and glioma research both nationally and internationally.

Profiles: Scopus 

Featured Publications

Kang, J., Xu, X., Tian, S., & Yang, G. (2025). Revisiting sinking skin flap syndrome: A series of case reports and literature review on cranioplasty with PEEK implants. Neurological Research, 47(2), 1–7.