Mahmoud Abd-Ellah | Computer Science | Best Researcher Award

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Assoc. Prof. Dr. Mahmoud Abd-Ellah | Computer Science | Best Researcher Award

Egyptian Russian University | Egypt

Dr. Mahmoud Khaled Abd-Ellah is an accomplished Assistant Professor at the Faculty of Artificial Intelligence, Egyptian Russian University, Badr, Egypt, widely recognized for his pioneering research at the intersection of artificial intelligence, medical imaging, and deep learning. Holding a Ph.D. in Electrical Engineering from Minia University, his doctoral research focused on brain tumor diagnosis through MRI using advanced machine learning techniques. His impressive publication portfolio includes 22 Scopus-indexed papers, collectively cited 830 times by 774 documents, with an h-index of 12 demonstrating substantial scientific impact and research excellence. His scholarly work has been featured in leading journals such as Scientific Reports, Neural Computing and Applications, and Ecological Informatics, advancing AI-driven approaches for medical image analysis, automated brain tumor detection, COVID-19 classification, and environmental data modeling. Beyond research, Dr. Abd-Ellah actively contributes to academic governance and quality enhancement as a member of the Egyptian International Ranking Committee, head of the Quality Management Unit, and ranking official at the Egyptian Russian University. He is also an active member of multiple IEEE councils, engaging in the development and application of AI across engineering and biomedical domains. His ORCID profile (0000-0002-6840-2503) and Scopus ID (57191265348) further reflect his consistent record of impactful scholarship and international collaboration. With his interdisciplinary expertise, editorial service, and mentorship of Ph.D. and master’s students, Dr. Mahmoud Khaled Abd-Ellah exemplifies academic leadership, innovation, and a transformative approach to research that advances both science and society.

Profile: Scopus | Google Scholar | ORCID | ResearchGate

Featured Publications

  • Abd-Ellah, M. K., Awad, A. I., Khalaf, A. A. M., & Hamed, H. F. A. (2019). A review on brain tumor diagnosis from MRI images: Practical implications, key achievements, and lessons learned. Magnetic Resonance Imaging, 61, 300–318.

  • Abd-Ellah, M. K., Awad, A. I., Khalaf, A. A. M., & Hamed, H. F. A. (2018). Two-phase multi-model automatic brain tumour diagnosis system from magnetic resonance images using convolutional neural networks. EURASIP Journal on Image and Video Processing, 2018(1), 1–10.

  • El-Rawy, M., Abd-Ellah, M. K., Fathi, H., & Ahmed, A. K. A. (2021). Forecasting effluent and performance of wastewater treatment plant using different machine learning techniques. Journal of Water Process Engineering, 44, 102380.

  • Abd-Ellah, M. K., Awad, A. I., Khalaf, A. A. M., & Hamed, H. F. A. (2016). Design and implementation of a computer-aided diagnosis system for brain tumor classification. In 2016 28th International Conference on Microelectronics (ICM) (pp. 73–76).

  • MostafaShokry, A. A. M. K., Awad, A. I., & Abd-Ellah, M. K. (2022). Systematic survey of advanced metering infrastructure security: Vulnerabilities, attacks, countermeasures, and future vision. Future Generation Computer Systems, 1–21.

Ruo Hu | Computer Science | Best Keynote Speaker

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Prof. Ruo Hu | Computer Science | Best Keynote Speaker

Guangdong Polytechnic Normal University | China

Professor Hu Ruo is a distinguished academician with a prolific background in artificial intelligence (AI) and medical image recognition. For over a decade, he has been leading graduate research in AI-driven medical diagnostics, with an emphasis on image-based disease classification and predictive systems. As a seasoned professor at Guangdong Polytechnic Normal University, his groundbreaking contributions have helped bridge clinical practice with intelligent systems, yielding innovations that benefit both academia and healthcare industries.

Professional profile👤

Scopus

Strengths for the Awards✨

Professor Hu Ruo brings a compelling blend of academic depth, technological innovation, and real-world collaboration that makes him exceptionally suitable for the “Best Keynote Speaker” award. With over a decade of leadership in AI-driven medical image recognition, his research is not only pioneering but also highly relevant to global health and AI advancements.

He holds three advanced degrees in computer science and information systems, complemented by long-standing teaching and research roles at esteemed Chinese institutions. His work spans key domains like deep learning, neuro-fuzzy systems, medical big data, and Internet of Things (IoT), with numerous peer-reviewed publications in top journals like Medical Physics and IEEE Transactions on Geoscience and Remote Sensing.

Prof. Hu has been PI of several government-funded high-impact projects, such as the Guangzhou Industry-University-Research Science & Tech project, with funding up to 2 million RMB, and has contributed to cross-sector collaborations with tech companies and hospitals. These collaborations have led to clinical applications, including tumor prediction systems and medical IoT platforms, underscoring his applied vision.

🎓 Education

Prof. Hu Ruo’s academic journey began with a Master of Science in Computer Science and Technology at Shaanxi Normal University (1987–1991). He then pursued a Master of Engineering in Computer Application at East China University of Science and Technology (1998–2002). Culminating his academic pursuits, he earned a Doctor of Management in Information System Management from the University of Shanghai for Science and Technology (2003–2006). His diverse interdisciplinary background forms a strong foundation for his research in AI applications.

🏢 Experience

Starting his career as a faculty member at the School of Mathematics and Computer Science, Ningxia University (1992–2007), Dr. Hu transitioned to the School of Computer Science, Guangdong Polytechnic Normal University in 2007. He was promoted to Associate Professor in 2006 and then to Full Professor in 2013. With over 30 years of teaching and research experience, he has played a pivotal role in shaping AI education and research methodologies in China.

🔬 Research Interests On Computer Science

Professor Hu’s research centers on AI in medical image recognition, big data semantic conflict resolution, neuro-fuzzy systems, and deep learning applications in disease diagnosis. He is particularly invested in the development of smart systems for tumor classification, sleep disorder diagnosis, and colorectal cancer detection. His work reflects a robust integration of knowledge-driven and data-driven models, contributing significantly to intelligent healthcare technologies.

🏅 Awards & Honors

Professor Hu Ruo has been the recipient of multiple prestigious research grants, including:

  • 2017 Guangzhou Industry-University-Research Major Science and Technology Project (¥2 million)

  • 2015 Guangdong Natural Science Foundation Project on big data and semantic conflict modeling (¥100,000)
    He has also received acclaim for his collaboration with high-tech companies and top medical institutions, cementing his reputation as a leader in interdisciplinary research.

📚 Selected Publications

Here are some of Professor Hu Ruo’s significant publications with citation details:

  1. Vision Transformer-based recognition of diabetic retinopathy grade, Medical Physics, 2021 — cited by numerous works in AI diagnostics.

  2. Diagnosis of sleep disorders in traditional Chinese medicine based on adaptive neuro-fuzzy inference system, Biomedical Signal Processing and Control, 2021 — contributed to fuzzy modeling in TCM.

  3. Research on data classification and feature fusion method of cancer nuclei image, International Journal of Imaging Systems and Technology, 2021 — applied deep learning in oncology.

  4. Locality Regularized Robust-PCRC framework for hyperspectral images, IEEE Transactions on Geoscience and Remote Sensing, 2020 — innovative feature extraction method.

  5. Key technologies for medical image knowledge discovery, International Journal of Pattern Recognition and Artificial Intelligence, 2020 — on intelligent knowledge systems.

  6. “A Mechanism for Healthy Big Data System Confliction Detection”, Basic & Clinical Pharmacology & Toxicology, 2016.

  7. “A New Efficiency Judging Method for Healthy Big Data”, Basic & Clinical Pharmacology & Toxicology, 2016.

  8. “Sensor Network Component Searching Method”, Journal of Investigative Medicine, 2015.

  9. “Semantic Data Network Analysis System”, Journal of Computer, 2013.

  10. “Stability Analysis of IoT Service via Data Stream Methods”, Applied Mathematics & Information Sciences, 2012.

🤝 Collaborations

Prof. Hu collaborated with Guangzhou Jinglian Information Technology Co., Ltd. to develop an AI-powered cloud platform for tumor prediction and postoperative classification. This was based on his earlier Guangdong-funded big data project. He also engaged in clinical-level partnerships with Sun Yat-sen University Cancer Prevention Center and Sixth Affiliated Hospital, providing valuable datasets and expertise for AI training and medical validation.

🎓 Supervision & Mentorship

Professor Hu has mentored numerous graduate theses, including work on deep learning for colorectal cancer, fuzzy systems for sleep disorders, and image-based diagnostics for lung and brain tumors. His students have published in top-tier journals and contributed to a total of 10 high-impact papers and 5 patents under his leadership.

🏁 Conclusion

In conclusion, Professor Hu Ruo exemplifies the spirit of innovation and interdisciplinary excellence. With a solid academic background, pioneering research in medical AI, and extensive industry and clinical collaborations, he stands out as a prime candidate for the Best Keynote Speaker. His work has not only advanced academic knowledge but also translated into tangible tools that enhance modern healthcare.