Wael Badawy | Computer Science | Best Researcher Award

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Prof. Dr. Wael Badawy | Computer Science | Best Researcher Award

Egyptian Russian University | Egypt

Prof. Wael Badawy, is a distinguished engineer, researcher, and academic leader with over 28 years of experience in higher education, research, technology commercialization, and innovation management. He earned his Ph.D. in Computer Engineering from the University of Louisiana at Lafayette, USA, and an equivalent Ph.D. in Electrical Engineering recognized by the Egyptian Higher Council of Universities, complemented by M.Sc. and B.Sc. degrees in Computer Science and Automatic Control Engineering from Alexandria University, Egypt. Prof. Wael Badawy has held senior academic and leadership positions, including Executive Director of ABM College, Canada, Program Head of Data Science and Cybersecurity at the Egyptian Russian University, and professorships at Nile University, Badr University, and the American University in Cairo, where he has taught and supervised students in Artificial Intelligence, Deep Learning, Multimedia Engineering, Cybersecurity, and Information Technology Management. His research contributions encompass over 400 publications in high-impact journals and conferences, 56 books and proceedings, and 34 co-invented patents, with highly cited work including the IEEE Transactions on Circuits and Systems for Video Technology (2018). Prof. Badawy has received more than 90 prestigious awards and honors, including the QS Reimagine Education Awards (2023, shortlisted), Silicon Review “30 Innovative Brands of the Year” (2022), and multiple distinctions in STEM, business innovation, and leadership. He actively serves on international standardization committees, professional organizations such as IEEE and ACM, and national research councils, contributing to curriculum development, program design, and strategic planning in higher education. Prof. Wael Badawy’s extensive contributions to research, innovation, and education demonstrate his sustained impact on technology, society, and the global academic community, making him an exemplary candidate for the Best Researcher Award.

Profile: Google Scholar | ORCID | LinkedIn | Staff Page

Featured Publications

  • Du, S., Ibrahim, M., Shehata, M., & Badawy, W. (2012). Automatic license plate recognition (ALPR): A state-of-the-art review. IEEE Transactions on Circuits and Systems for Video Technology, 23(2), 311–325.

  • Rahman, C. A., Badawy, W., & Radmanesh, A. (2003). A real-time vehicle’s license plate recognition system. In Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance.

  • Shehata, M. S., Cai, J., Badawy, W. M., Burr, T. W., Pervez, M. S., Johannesson, R. J., … (2008). Video-based automatic incident detection for smart roads: The outdoor environmental challenges regarding false alarms. IEEE Transactions on Intelligent Transportation Systems, 9(2), 349–360.

  • Ghallab, Y. H., Badawy, W., Kaler, K. V. I. S., & Maundy, B. J. (2005). A novel current-mode instrumentation amplifier based on operational floating current conveyor. IEEE Transactions on Instrumentation and Measurement, 54(5), 1941–1949.

  • Du, S., Shehata, M., & Badawy, W. (2011). Hard hat detection in video sequences based on face features, motion and color information. In 2011 3rd International Conference on Computer Research and Development, 4, 25–29.

  • Ghallab, Y., & Badawy, W. (2004). Sensing methods for dielectrophoresis phenomenon: From bulky instruments to lab-on-a-chip. IEEE Circuits and Systems Magazine, 4(3), 5–15.

  • Badawy, W., & Gomaa, H. (2015). Analyzing a segment of video. U.S. Patent No. 9,014,429.

  • Ghallab, Y. H., & Badawy, W. (2010). Lab-on-a-chip: Techniques, circuits, and biomedical applications. Artech House.

  • Badawy, W. (2009). Mesh based frame processing and applications. U.S. Patent No. 7,616,782.

  • Badawy, W. (2009). Video based monitoring system. U.S. Patent No. 7,612,666.

Jiajie Gao | Computer Science | Best Researcher Award

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Mr. Jiajie Gao | Computer Science | Best Researcher Award

Hebei University of Architecture | China

Gao Jiajie is a highly driven and innovative researcher currently pursuing a master’s degree at Hebei University of Architecture. In just two years, he has demonstrated exceptional research prowess by independently publishing three SCI Q3 journal articles, authoring 16 software patents, and leading a national-level project. His commitment to bridging theoretical AI innovations with real-world applications places him at the forefront of emerging research talent in occupational safety and intelligent detection systems.

Professional profile👤

Scopus

Strengths for the Awards✨

Gao Jiajie demonstrates exceptional research performance, particularly notable given his status as a master’s student. His achievements include publishing three SCI Q3 journal articles, securing 16 authorized software patents, and acting as principal investigator on a national-level project—a feat typically rare at this early career stage. His research focuses on applied artificial intelligence in safety-critical systems, such as railway worker compliance, power grid integrity, and smart retail. Gao’s innovation in improving YOLOv5-based detection systems—including integrating CBAM and MPDIoU modules—shows deep technical insight and a solutions-oriented mindset. Moreover, his ability to translate research into real-world industrial collaborations speaks to his applied impact, with outputs in railway safety, insulator fault detection, and retail inventory management. His role as a reviewer for a peer-reviewed journal further highlights his growing reputation in the academic community. 🔍

🎓 Education

Gao Jiajie is presently a master’s student at Hebei University of Architecture, where he is actively involved in cutting-edge research in artificial intelligence and its applications in safety systems. His academic journey is marked by a strong focus on practical innovations and scholarly contributions, showcasing an excellent balance between theory and implementation.

💼 Experience

In his short academic career, Gao Jiajie has already led one national-level project as the principal investigator and served as a key contributor in multiple collaborative initiatives. His leadership resulted in eight authorized software patents and several AI-based detection systems. He also actively participates in academic review processes as a reviewer for the Journal of Electronic Imaging (JEI).

🧠 Research Interest On Computer Science

Gao’s research centers on Artificial Intelligence, particularly in the development of advanced detection algorithms that enhance occupational safety and industrial automation. His innovative approach integrates attention mechanisms (CBAM), improved loss functions (MPDIoU), and real-time object detection models (YOLOv5/YOLOv8), delivering significant accuracy improvements in challenging environments such as railways, power grids, and retail sectors.

🏅 Awards

While still early in his academic journey, Gao Jiajie’s work has garnered national recognition. His role as Principal Investigator of a national-level project, along with his multiple patents and peer-reviewed publications, highlight his merit for the Best Researcher Award. His work stands as a testament to innovation, application, and academic excellence. 🏆

📚 Publications

Gao Jiajie has published three peer-reviewed SCI Q3 journal articles, each making notable contributions to AI-based visual detection systems:

  1. Gao, Jiajie, et al. Safety equipment compliance analysis for occupational safety, Signal, Image and Video Processing, Vol. 19, Article 720, 2025.
    📈 Cited by: Article recently published; citation data forthcoming.

  2. Gao, Jiajie, et al. Enhanced YOLOv8 for high-precision retail cabinet product recognition, Signal, Image and Video Processing, Vol. 19.7, 2025.
    📈 Cited by: 2 articles.

  3. Gao, Jiajie, et al. Research on the algorithm of detecting insulators in high-voltage transmission lines using UAV images, Signal, Image and Video Processing, Vol. 18, Suppl 1, 2024.
    📈 Cited by: 5 articles.

These publications emphasize Gao’s skill in applying deep learning techniques to complex detection challenges in infrastructure and retail environments.

✅ Conclusion

Gao Jiajie exemplifies the qualities of a forward-thinking researcher, blending deep technical knowledge with practical implementation in AI-based safety systems. His rapid output of publications, patents, and leadership in a national project underscores a rare level of maturity, innovation, and commitment at an early academic stage. With outstanding contributions in detection algorithm design, academic reviewing, and cross-sector collaboration, Gao is a deserving nominee for the Best Researcher Award.