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.

Assoc. Prof. Dr. Wenbo Shen | Computer Science and Artificial Intelligence | Best Researcher Award

Zhejiang University | China

Dr. Wenbo Shen is a tenured Associate Professor at the College of Computer Science and Technology, Zhejiang University. He is a highly regarded researcher in computer software and system protection, with expertise in program analysis, operating system security, and energy-efficient system defense. With a career spanning academia and industry, Dr. Shen has established himself as an innovative scholar whose work has advanced the field of computer security on a global scale.

Professional Profile

Scopus

Google Scholar

ORCID

Education

Dr. Wenbo Shen earned his Ph.D. in Computer Science from North Carolina State University, where his dissertation focused on wireless security and physical layer signal design under the supervision of distinguished professors. Prior to this, he obtained his Bachelor of Science degree in Software Engineering from the Harbin Institute of Technology, graduating in the top tier of his class. This solid academic foundation has shaped his excellence in research and teaching.

Experience

Dr. Wenbo Shen’s professional journey reflects a balance of academic leadership and industrial innovation. He began his career as a Senior Research Scientist at Samsung Research America, where he contributed to advanced security solutions for operating systems. He later joined Zhejiang University, first as an Assistant Professor and then progressing to a tenured Associate Professor. His teaching and supervision experience has nurtured the next generation of scholars, while his leadership in funded research projects has strengthened collaborations between academia and industry.

Research Interest

Dr. Wenbo Shen’s research focuses on protecting computer software and systems through advanced program analysis techniques. His contributions span detecting software bugs in major operating systems such as Linux, FreeBSD, and Fuchsia, while also developing lightweight protection mechanisms for mobile systems, containerized environments, and edge computing. He is particularly known for creating resource- and energy-friendly defense strategies, bridging theoretical innovation with practical application in real-world computing systems.

Awards

Dr. Wenbo Shen has been recognized with multiple Distinguished Paper Awards from top international security conferences, including the European Symposium on Research in Computer Security, the Annual Computer Security Applications Conference, ACM Asia Conference on Computer and Communications Security, and the Network and Distributed System Security Symposium. These honors highlight the significance and impact of his research contributions in advancing secure computing.

Publication

Dr. Wenbo Shen has contributed extensively to high-impact journals and conferences in computer security, with his works widely cited by international researchers.

Title: Hypervision across worlds: Real-time kernel protection from the arm trustzone secure world
Published on: 2014
Citation: 400
Title: SKEE: A lightweight Secure Kernel-level Execution Environment for ARM
Published on: 2016
Citation: 126
Title: Ally friendly jamming: How to jam your enemy and maintain your own wireless connectivity at the same time
Published on: 2013
Citation: 101
Title: {PeX}: A permission check analysis framework for linux kernel
Published on: 2019
Citation: 98
Title: Is link signature dependable for wireless security?
Published on: 2013
Citation: 75
Title: Ptrix: Efficient hardware-assisted fuzzing for cots binary
Published on: 2019
Citation: 68
Title: NORAX: Enabling execute-only memory for COTS binaries on AArch64
Published on: 2017
Citation: 65

Conclusion

Dr. Wenbo Shen’s career reflects excellence in scholarship, innovation in security research, and dedication to advancing computer system protection. His pioneering contributions in operating system defense, his recognition through prestigious international awards, and his consistent high-impact publications make him a deserving nominee for the Best Researcher Award. His work continues to influence the field globally, shaping both academic research and practical applications in secure computing.