Bingqin Han | Computer Science and Artificial Intelligence | Research Excellence Award

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Mr. Bingqin Han | Computer Science and Artificial Intelligence | Research Excellence Award

Tianjin University | China

Mr. Bingqin Han, is a leading researcher at the intersection of artificial intelligence, consumer psychology, and business ethics, focusing on the factors that influence AI adoption in both consumer and managerial contexts. His work integrates behavioral science, marketing, and technology studies to examine how trust, risk perception, ethical considerations, and cognitive biases shape the acceptance and utilization of AI technologies. He has pioneered innovative frameworks for modeling human–AI interaction, most notably the “onion model” of AI humanoid robot adoption in domestic settings, which conceptualizes acceptance across technical, psychological, and social layers, offering both theoretical and practical insights. Mr. Bingqin Han’s scholarly contributions include three peer-reviewed publications, which have garnered three citations and an h-index of 1 according to Scopus, reflecting his emerging influence in the field. Beyond publications, he has contributed to interdisciplinary research projects, participated in editorial and peer-review activities, and engaged in collaborative initiatives that bridge academia and industry, highlighting his commitment to advancing both theory and practice. His work has significantly enriched understanding of human–AI integration, providing actionable guidance for developers, policymakers, and researchers aiming to optimize AI deployment in real-world environments. By combining rigorous empirical research, innovative conceptual frameworks, and interdisciplinary collaboration, Han has made substantial contributions to AI adoption research, behavioral decision-making, and ethical technology development, establishing a foundation for future innovations and informing responsible, human-centered implementation of AI technologies across diverse contexts.

Profile: Scopus

Featured Publications

  • Han, B., Song, S., Liu, D., & Mo, J. (2024). Mechanism of online public opinion formation in major risk events in China: A qualitative comparative analysis.

  • Han, B., & Liu, D. (2025). Peeling back acceptance: An onion model of AI humanoid robot adoption in homes.

 

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.

Ozgur Tonkal | Computer Science and Artificial Intelligence | Best Researcher Award

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Assoc. Prof. Dr. Ozgur Tonkal | Computer Science and Artificial Intelligence | Best Researcher Award

Samsun University | Turkey

Dr. Ozgur Tonkal is a distinguished academician and researcher at Samsun University, specializing in cybersecurity, Software-Defined Networks (SDN), and AI-driven threat detection. He earned his Ph.D. in Computer Engineering from Gazi University in 2022, where his doctoral research introduced an autonomous intrusion detection and mitigation model for SDN, providing adaptive and traffic-aware defense against volumetric attacks. Building on this foundation, he developed a multimodal spam email detection framework that integrates Distil BERT embeddings with structural features, achieving 99.62% accuracy and exposing concept drift vulnerabilities across eras of spam. Dr. Ozgur Tonkal has contributed significantly to both academic research and practical applications through international journal articles, conference papers, and book chapters that advance explainable and continually learning cybersecurity systems. His completed research includes DDoS detection using machine learning and neighborhood component analysis, while ongoing projects focus on adaptive spam detection, IoT traffic analysis, and explainable deep learning models for robust network security. Beyond academia, he serves as ISO/IEC 27001:2022 Lead Auditor, coordinator of a university Cyber Incident Response Team, and technical advisor for the Ministry of Education International Robotics Competition, demonstrating his ability to translate research into real-world solutions. Notable publications include studies on multimodal spam detection, AI-based dementia diagnosis, and DDoS attack detection in SDN. Dr. Ozgur Tonkal exemplifies excellence in research, innovation, and the practical implementation of cybersecurity solutions.

Profile: Google Scholar | ORCID | ResearchGate | LinkedIn | Staff Page

Featured Publications

  • Tonkal, Ö., Polat, H., Başaran, E., Cömert, Z., & Kocaoglu, R. (2021). Machine learning approach equipped with neighbourhood component analysis for DDoS attack detection in software-defined networking. Electronics, 10(1227), 1–18. Cited by 128.

  • Tonkal, Ö., & Polat, H. (2021). Traffic classification and comparative analysis with machine learning algorithms in software-defined networks. Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji, 9(1), 1–12. Cited by 15.

  • Sertkaya, M. E., Ergen, B., Türkoğlu, M., & Tonkal, Ö. (2024). Accurate diagnosis of dementia and Alzheimer’s with deep network approach based on multi‐channel feature extraction and selection. International Journal of Imaging Systems and Technology, 34(3), e23079. Cited by 4.

  • Ouhsousou, S., & Tonkal, Ö. (2024). Analysis of global language dynamics: A cross-cultural examination of the most spoken languages and perceived learning ease. 8th International Artificial Intelligence and Data Processing Symposium, 1–6. Cited by 1.

  • Selimdaroğlu, Y., Yusuf, & Tonkal, Ö. (2025). Acil durum çağrı merkezi uygulamalarında kullanıcı memnuniyeti ve performans analizi: 112 örneği. International Journal of Advances in Engineering and Pure Sciences, 37(2), 45–60.

Umaeswari P | Computer Science | Best Researcher Award

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Dr. Umaeswari P | Computer Science | Best Researcher Award

R.M.K. Engineering College | India

Dr. P. Umaeswari is an accomplished academician and researcher in the field of Computer Science and Engineering with over 18 years of professional experience. Currently serving as an Associate Professor at R.M.K. Engineering College, Chennai, she has made significant contributions to advanced computing and interdisciplinary research. With a strong academic foundation and a deep commitment to educational excellence, she continuously strives to align academic innovation with societal needs.

Professional profile👤

Google Scholar

ORCID

Scopus

Strengths for the Awards✨

Dr. P. Umaeswari is a distinguished academician and researcher with over 18 years of rich teaching and research experience in Computer Science and Engineering. Her remarkable trajectory across various reputed institutions highlights her dedication to advancing technical education and research excellence.

She has published 30+ impactful international journal papers, including prestigious outlets like Springer, IEEE Xplore, Elsevier, and UGC CARE journals, demonstrating interdisciplinary depth in IoT, Cloud Computing, Machine Learning, Cybersecurity, and Bioinformatics. Her work on biosensors, privacy in wearable IoT devices, smart agriculture, and AI-based security systems shows a strong alignment with current technological challenges and innovations.

In addition to research papers, Dr. Umaeswari has authored six academic books on topics ranging from Artificial Intelligence to Network Security, enhancing curriculum resources and bridging the academic-industry gap. Furthermore, her professional memberships in organizations such as ISTE, Indian Academic Researchers Association, and Knowledge Research Academy reinforce her credibility and active engagement with the research community.

🎓 Education

Dr. Umaeswari holds a Ph.D. in Computer Science and Engineering from St. Peter’s University (2019), preceded by an M.E. in the same field from the same institution (2011). She also earned an M.Phil. in Computer Science (2009) and an M.C.A. in Computer Applications (2006) from Alagappa University. Her academic journey began with a B.Sc. in Computer Science (2000) from Bhaktavatsalam Memorial College for Women under Madras University. Her consistent pursuit of excellence is evident in her academic accolades and grades.

💼 Professional Experience

Dr. Umaeswari’s career spans across various esteemed institutions. She is currently an Associate Professor at R.M.K. Engineering College (2022–present). Her earlier roles include Assistant Professorships at S.A. College of Arts & Science, Mar Gregorios College, and Ponnusamy Nadar College, among others. With 18 years and 3 months of teaching experience, her roles have encompassed teaching, mentoring, and research. Her long-standing service in both engineering and arts and science colleges highlights her interdisciplinary flexibility and dedication.

🔬 Research Interests On Computer Science

Dr. Umaeswari’s research interests encompass Machine Learning, IoT, Cloud Computing, Cybersecurity, Bioinformatics, and Smart Systems. Her work aims at integrating theoretical computing concepts with real-world applications such as biosensors, smart agriculture, and secure cloud frameworks. Her multi-domain approach empowers interdisciplinary collaboration and innovation.

🏆 Awards

Dr. Umaeswari has been honored with numerous accolades including the Research Excellence Award (2024) from SIDVI Foundation, the Inspiring Research Associate Award (2023) from Madras Journal Series Pvt Ltd, and two Best Faculty Awards (2022 & 2023) from prominent academic bodies. These recognitions validate her impact in academia and innovation.

📚 Publications

Dr. Umaeswari has contributed to over 30 international journals and numerous conferences. Her recent impactful works include:

  • Machine Learning Based Predicting the Assisted Living Care Needs
    P. Umaeswari, S.B.G.T. Babu, G.A. Sankaru, G.N.R. Prasad, B.V.S. Thrinath, …
    2022 — 📑 48 citations

  • Development of Programmed Autonomous Electric Heavy Vehicle: An Application of IoT
    P.N. Reddy, P. Umaeswari, L. Natrayan, A. Choudhary
    2023 — 📑 19 citations

  • Statistical Computing and Analysis of Apple Peel Biocarbon and Beta Vulgaris Cellulosic Fiber Vinyl-Based EMI Shielding Composite
    P. Umaeswari, G. Lokesh, A.S.A. Nisha, I.J. Solomon
    2025 — 📑 6 citations

  • IoT-Enabled Energy Conservation in Residential Buildings: Machine Learning Models for Analyzing Annual Solar Power Consumption
    P. Umaeswari, R. Sonia, T.R. Saravanan, N. Poyyamozhi
    2024 — 📑 6 citations

  • Development of Innovative Algorithm for Sound Detection Based on FFT and Goertzel Algorithms
    P. Umaeswari, B.V. Jyothi, G.R.G. King, T. Patil, R. Gukendran
    2024 — 📑 3 citations

  • Internet of Things (IoT) for Remote Earthquake and Fire Detection Monitoring: Linking Safety
    P. Umaeswari, M. Muktasandhu, M. Vignesh, R. Ramyamaranan, …
    2024 — 📑 2 citations

  • Digital Twin-Driven Intrusion Detection for IoT and Cyber-Physical System
    S.K. Ramamoorthy, L. Sindhu, K. Valarmathi, C. Gobinath, P. Umaeswari
    2024 — 📑 1 citation

  • Strategic Management Accounting Practices Between Developed and Emerging Economies Using Machine Learning
    M.S. Almahairah, V.K. Saroha, A. Asokan, P. Umaeswari, J.A. Khan, …
    2022 — 📑 1 citation

  • Local Train Ticketing System Using Web Services
    R. Sheeja, P. Umaeswari, C. Bibin, R. Nishanth, S.H. Chandana
    2022 — 📑 1 citation

  • Multilevel Security System for Big Data Cloud Using SDBS Algorithm
    P. Umaeswari, B. Shanthini, S. Senthil Kumar
    2020 — 📑 1 citation

📝 Conclusion

Dr. P. Umaeswari stands out as a passionate educator, prolific researcher, and visionary thinker. With numerous accolades, interdisciplinary research, impactful publications, and two decades of academic service, she embodies the ideal candidate for a prestigious award. Her scholarly impact and dedication to continuous improvement ensure that she will continue to elevate the fields of Computer Science and Engineering.