Prof. Dr. Chengli Sun | Artificial Intelligence | Best Researcher Award

Published on 09/12/202509/12/2025 by Superior Awards

Prof. Dr. Chengli Sun | Artificial Intelligence | Best Researcher Award

Prof. Dr. Chengli Sun | Guangzhou Maritime University | China

Prof. Dr. Chengli Sun is a distinguished scholar in the field of signal and information processing, widely recognized for his significant contributions to intelligent acoustic technology and next-generation speech systems.To date, his work has accumulated 336 citations across 303 documents, demonstrating the broad recognition and adoption of his research outcomes by both domestic and international peers. With 46 published documents spanning high-impact journals His research encompasses speech recognition, speech enhancement, acoustic scene analysis, and computer vision, with a strong focus on advancing human–machine voice interaction under complex and noisy environments. He has led a series of high-impact scientific projects, including major National Natural Science Foundation of China grants and key provincial and municipal initiatives, driving breakthroughs in generative adversarial network models, dual-diffusion speech enhancement, sustainable learning-oriented vehicle voice interaction, and speaker-specific keyword spotting. These research outcomes have enabled practical advancements in intelligent transportation, robotics, smart devices, and public safety. Alongside his research achievements, Prof. Dr. Chengli Sun plays an integral role in academic development and scientific service by contributing to expert review committees and supporting the progress of information processing and acoustics disciplines. He remains committed to high-level talent cultivation through leadership in first-class undergraduate teaching programs and the promotion of interdisciplinary innovation in artificial intelligence and signal processing. Collectively, his sustained research efforts, academic influence, and dedication to education position him as a leading figure shaping the future of intelligent voice technologies.

Profiles: Scopus | Orcid

Featured Publications

Sun, M., Sun, C., Zou, C., Zhang, J., & Xiang, D. (2025). Modeling of multi-electrode epicardial electrograms for conductivity estimation in atrial fibrillation. IEEE Access.
Li, J., Xiang, D., Li, C., Mao, S., Chen, Y., Sun, M., He, W., Deng, Y., & Sun, C. (2025, December 3). Learning student knowledge states from multi-view question–skill networks. Symmetry.
Leng, Y., Zhang, E., Zhuang, J., Shen, C., Sun, C., Yuan, Q., & Pan, J. (2025, October). A topic-specific representation learning framework for acoustic scene classification. Applied Soft Computing.
Rao, Z., Sun, C., Sun, J., Chen, F., Leng, Y., Sun, M., & Guo, Q. (2025, October 16). A new speech enhancement model based on residual denoising diffusion. Circuits, Systems, and Signal Processing.
Wan, M., Zhu, J., Sun, C., Yang, Z., Yin, J., & Yang, G. (2024). Tensor low-rank graph embedding and learning for one-step incomplete multi-view clustering. IEEE Transactions on Multimedia.

Prof. Ebenezer Esenogho | Artificial Intelligence | Best Researcher Award

Published on 19/11/202519/11/2025 by Superior Awards

Prof. Ebenezer Esenogho | Artificial Intelligence | Best Researcher Award

Prof. Ebenezer Esenogho | University of South Africa | South Africa

Prof. Ebenezer Esenogho (NRF C2-rated) is a distinguished academic and research leader recognized for his extensive contributions to Artificial Intelligence, telecommunications engineering, and digital innovation. With a strong background in computer, electronics, and communication engineering, he has built an influential career marked by advanced research, academic leadership, and international collaboration. He has produced impactful work across areas such as AI-driven wireless systems, 5G networks, cognitive radio, cybersecurity, IoT, smart grid technologies, software-defined systems, big data, and cloud computing. His scholarly influence is reflected in 920 citations from 762 documents, 40 published documents, and an h-index of 12. Prof. Esenogho has secured numerous competitive grants, awards, and research fellowships in recognition of his excellence, and he has contributed to global research advancement through participation in strategic committees, collaborative initiatives, and high-level innovation programs. He has supervised a wide portfolio of postgraduate researchers, contributed to editorial boards, reviewed international grant proposals, and chaired sessions at reputable conferences. Beyond research, he is committed to academic mentorship, capacity building, and advancing technology-driven development through community-focused initiatives. Prof. Ebenezer continues to play a leading role in shaping the future of intelligent systems, next-generation networks, and multidisciplinary innovation across regional and global research landscapes.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Esenogho, E., Mienye, I. D., Swart, T. G., Aruleba, K., & Obaido, G. (2022). A neural network ensemble with feature engineering for improved credit card fraud detection. IEEE Access, 10, 16400–16407.
Esenogho, E., Djouani, K., & Kurien, A. M. (2022). Integrating artificial intelligence, Internet of Things, and 5G for next-generation smart grid: A survey of trends, challenges, and prospects. IEEE Access, 10, 4794–4831.
Sarah, I. D. M., Ebiaredoh-Mienye, A., Esenogho, E., & Swart, T. G. (2022). A machine learning method with filter-based feature selection for improved prediction of chronic kidney disease. Bioengineering, 9(8).
Nguyen, N., Duong, T., Chau, T., Nguyen, V. H., Trinh, T., Tran, D., Ho, T., … Esenogho, E. (2022). A proposed model for card fraud detection based on CatBoost and deep neural network. IEEE Access, 10, 96852–96861.
Arnaz, A., Lipman, J., Abolhasan, M., Hiltunen, M., … Esenogho, E. (2022). Toward integrating intelligence and programmability in open radio access networks: A comprehensive survey. IEEE Access, 10, 67747–67770.
Obaido, G., Ogbuokiri, B., Swart, T. G., Ayawei, N., Kasongo, S. M., Aruleba, K., … Esenogho, E. (2022). An interpretable machine learning approach for hepatitis B diagnosis. Applied Sciences, 12(21), 11127.

Mr. Eze Jude Uche | Artificial Intelligence | Best Researcher Award

Published on 22/09/202526/09/2025 by Superior Awards

Mr. Eze Jude Uche | Artificial Intelligence | Best Researcher Award

Mr. Eze Jude Uche | The Ohio State University College of Pharmacy | United States

Mr. Eze Jude Uche is a dedicated and accomplished researcher in pharmacoepidemiology, patient-reported outcomes, cancer therapy, infection prevention, and predictive modeling. He is currently pursuing a PhD in Health Services & Outcomes Research at The Ohio State University College of Pharmacy, where he is recognized as a Dean’s Distinguished Fellow and receives advanced training in pharmacoepidemiology, biostatistics, survival analysis, causal inference, and bioinformatics. He holds a Bachelor of Pharmacy (BPharm) from the University of Nigeria, Nsukka, with a distinction in Pharmacy Administration and Management; his thesis focused on assessing malaria treatment patterns and costs in community pharmacies and patent medicine shops in Nsukka and Enugu. He has 2 published documents to his credit. Mr. Uche has extensive research experience, including a tenure as a Graduate Research Assistant and Intern Pharmacist at the National Institute for Pharmaceutical Research and Development in Abuja, where he conducted comprehensive literature reviews, analyzed and interpreted experimental results, and authored detailed research reports. His hands-on experience spans microbial preparation, standardization of bacteria and Candida species, extraction of plant materials, chromatographic separation for pharmacologic screening, in-vitro drug testing using animal models, and qualitative and quantitative pharmaceutical analysis, reflecting a strong commitment to advancing pharmaceutical and healthcare research.

Profile: Scopus

Featured Publication

Uche, E. J.,(2025). Optimizing unsupervised feature engineering and classification pipelines for differentiated thyroid cancer recurrence prediction. BMC Medical Informatics and Decision Making. Advance online publication.

Prof. Dr. Liudmyla Tereikovska | Neural Network Applications | Cybersecurity Excellence Award

Published on 03/03/202503/03/2025 by Superior Awards

Prof. Dr. Liudmyla Tereikovska | Neural Network Applications | Cybersecurity Excellence Award

Prof. Dr. Liudmyla Tereikovska , Kyiv National University of Construction and Architecture , Ukraine.

Prof.Dr. Liudmyla Tereikovska, is a distinguished Ukrainian scientist in information technology and cybersecurity. She holds a Ph.D. in Technical Sciences and a Doctor of Technical Sciences degree. Currently, she is a Professor at Kyiv National University of Construction and Architecture. Her expertise spans information security, voice signal recognition, biometric authentication, and cybersecurity. Passionate about innovation, she has contributed significantly to the field through extensive research and teaching. With a deep commitment to technological advancement, she continues to inspire future generations in the IT sector.

Publication Profile

Scopus

Orcid

Education & Experience

MSc in Technological Engineering – State Academy of Light Industry of Ukraine (1997)
Ph.D. in Technical Science – Kyiv National University of Construction and Architecture (2016)
Doctor of Technical Sciences (Dr. Eng.) – National Transport University (2023)
Professor of Information Technology Design & Applied Mathematics (2024)

Professional Experience:

2023 – Present: Professor, Kyiv National University of Construction and Architecture
2019 – 2023: Associate Professor, Kyiv National University of Construction and Architecture
2019 – 2021: Doctoral Student, Kyiv National University of Construction and Architecture
2017 – 2019: Associate Professor, Department of Cybersecurity & Computer Engineering
2012 – 2016: Postgraduate Student, Kyiv National University of Construction and Architecture
2010 – 2012: Assistant, Department of Information Technologies
2004 – 2010: Assistant, Department of Informatics & Control Systems

Suitability summary

Prof.Dr. Liudmyla Tereikovska, is a highly esteemed researcher in cybersecurity and information technology, making her a strong candidate for the Cybersecurity Excellence Award. With a Doctor of Technical Sciences degree and extensive experience in biometric authentication, facial recognition, and AI-driven cybersecurity solutions, she has significantly contributed to enhancing digital security frameworks. Her research has played a crucial role in developing intelligent security systems, voice signal recognition, and emotion detection, ensuring innovative advancements in critical infrastructure protection. Her dedication to cutting-edge technology has had a profound impact on biometric authentication methods and AI-based cybersecurity solutions.

Professional Development

Prof.Dr. Liudmyla Tereikovska, has made remarkable strides in the field of cybersecurity and information technology. With expertise in voice signal recognition, biometric authentication, and intelligent information security systems, she has contributed extensively to research and education. As a Professor, she mentors students, shaping the next generation of IT professionals. Her commitment to technological advancements is reflected in her research on emotion recognition and cyber protection. Dedicated to innovation, she collaborates on international projects and continuously develops advanced cybersecurity solutions. Her work significantly impacts the future of digital security and AI-driven authentication.

Research Focus

Prof.Dr. Liudmyla Tereikovska, research delves into cutting-edge cybersecurity advancements, biometric authentication, and artificial intelligence applications. She specializes in voice signal recognition, emotion detection, and intelligent security systems, ensuring innovative solutions in cyber protection. Her work also explores AI-driven biometric authentication, enhancing security measures in digital environments. With a keen interest in data protection and cryptographic technologies, she develops smart solutions for safeguarding sensitive information. Collaborating on global projects, she contributes to enhancing cybersecurity frameworks worldwide. Her research directly influences next-gen security technologies and AI-driven risk detection systems.

Awards & Honors

Associate Professor Diploma – Department of Cybersecurity & Computer Engineering (2018)
Doctor of Technical Sciences Degree – National Transport University (2023)
Professor Title – Department of Information Technology Design & Applied Mathematics (2024)
Recognized for Excellence in Cybersecurity Research
Honored for Contributions to Biometric Authentication and AI Development

Publication Top Notes

“Modular Neural Network Model for Biometric Authentication of Personnel in Critical Infrastructure Facilities Based on Facial Images” – Applied Sciences (2025) | DOI: 10.3390/app15052553

“Conceptual model of the face recognition process based on the image of the face and iris of personnel of critical infrastructure facilities” – Conference Paper (2024) | DOI: 10.23939/IW_itpm2024.278

“Концептуальна модель процесу прогнозування навантаження на вебсервер” – Computer-Integrated Technologies: Education, Science, Production (2024) | DOI: 10.36910/6775-2524-0560-2024-54-09

“Multiple Effectiveness Criteria of Forming Databases of Emotional Voice Signals” – Cybersecurity: Education, Science, Technique (2023) | DOI: 10.28925/2663-4023.2023.21.6574

“Infrastructure Projects of Road Traffic Management: Management Methodology Selection” – Management of Development of Complex Systems (2023) | DOI: 10.32347/2412-9933.2023.56.24-30

Conclusion

Prof.Dr. Liudmyla Tereikovska, outstanding contributions to cybersecurity, biometric authentication, and AI-driven security systems make her an ideal recipient of the Best Researcher Award. Her research not only strengthens global cybersecurity standards but also drives forward next-generation technological advancements. Through her groundbreaking work, publications, and leadership in academia, she continues to shape the future of information security and artificial intelligence. .