Abdultaofeek Abayomi | Machine Learning | Best Researcher Award

Dr. Abdultaofeek Abayomi | Machine Learning | Best Researcher Award

Researcher at Walter Sisulu University, South Africa

ABDULTAOFEEK ABAYOMI, Ph.D., is a distinguished academic and researcher with a rich career in Information Technology and Computer Science. He holds a Ph.D. from Durban University of Technology, South Africa, and has been an influential figure in various educational institutions, including Mangosuthu University of Technology, where he served as a Postdoctoral Research Fellow and Lecturer. His extensive experience spans roles in teaching, research, and industry, with a specific focus on ICT, machine learning, and telecommunications. Dr. Abayomi’s contributions extend beyond academia, having held positions in major banks and IT firms, where he influenced projects in system analysis, IT infrastructure, and banking operations.

Profile

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Education

Dr. Abayomi’s academic journey began with a B.Sc. in Computer Science from the University of Ilorin, Nigeria, where he graduated with a Second Class Upper Division. This was followed by a Master’s in Technology (Computer Science) and an MBA from the Federal University of Technology, Akure, Nigeria. He then pursued a Ph.D. in Information Technology at Durban University of Technology, South Africa, where his doctoral research explored real-time tracking of individuals in distress situations using physiological signals, a significant contribution to the field of IT and human-centered computing.

Experience

Dr. Abayomi’s professional career spans teaching, research, and leadership roles in the technology sector. He has lectured and conducted research at various universities, including Durban University of Technology and Mangosuthu University of Technology in South Africa. Additionally, he has worked as a system analyst and instructor for IT certifications such as MCSE and MCSA at JIT Solutions in Akure, Nigeria. His career in the banking sector includes roles as a Profit Centre Manager and ICT System Administrator at United Bank for Africa Plc., where he contributed to improving operational efficiency and implementing IT solutions. Dr. Abayomi has also been involved in research projects aimed at addressing pressing issues in ICT and society, particularly focusing on the intersection of technology and human needs.

Research Interests

Dr. Abayomi’s research interests lie at the convergence of Information Technology, machine learning, and network systems. His work has explored deep learning, cognitive radio networks, spectrum sensing, and software-defined networks. He is particularly interested in the application of artificial intelligence to solve real-world problems, such as dynamic spectrum access and health insurance prediction. Dr. Abayomi’s research aims to improve the way technology interacts with human and environmental factors, making significant contributions to both academic and applied research.

Awards

Dr. Abayomi has received numerous accolades in recognition of his academic and research excellence. He was honored with the Research Award for Most Productive Postdoctoral Research Fellow in 2022 at Mangosuthu University of Technology, South Africa. He has also been an active participant in international conferences, serving as a session chair for various events such as the 22nd International Conference on Hybrid Intelligent Systems in 2022 and the 13th International Conference on Soft Computing and Pattern Recognition in 2021. His contributions to research are further exemplified by his involvement in winning the South African National Research Foundation’s Infrastructure Bridging Funding in 2016.

Publications

Dr. Abayomi’s scholarly work is well-regarded in academic circles, with several impactful publications in peer-reviewed journals. His notable publications include:

Ukpong, U.C., Idowu-Bismark, O., Adetiba, E., Kala, J.R., Owolabi, E., Oshin, O., Abayomi, A., Dare, O.E. (2025). “Deep reinforcement learning agents for dynamic spectrum access in television whitespace cognitive radio networks.” Scientific African, 27, e02523.

Dare, O.E., Okokpujie, K., Adetiba, E., Idowu-Bismark, O., Abayomi, A., Kala, R.J., Owolabi, E., Ukpong, U.C. (2024). “Development of a Conditional Generative Adversarial Network Model for Television Spectrum Radio Environment Mapping.” IEEE Access, 12, 197632-197644.

Mavundla, K., Thakur, S., Adetiba, E., Abayomi, A. (2024). “Predicting Cross-Selling Health Insurance Products Using Machine-Learning Techniques.” Journal of Computer Information Systems.

Adetiba, E., Uzoatuegwu, P.C., Ifijeh, A.H., Abayomi, A., Obiyemi, O. (2024). “NomadicBTS-2: A Network-in-a-Box with Software-Defined Radio and Web Based App for Multiband Cellular Communication.” International Journal of Computing and Digital Systems, 15(1), 1-16.

Aroba, O.J., Abayomi, A. (2023). “An Implementation of SAP Enterprise Resource Planning – A Case Study of the South African Revenue Services and Taxation Sectors.” Cogent Social Sciences.

These publications reflect his diverse research interests and his significant impact on fields ranging from telecommunications to machine learning and health technology.

Conclusion

Dr. Abayomi’s academic and professional journey is a testament to his dedication to advancing knowledge in Information Technology and its application to solving societal challenges. His work has influenced both the academic community and industry practices, particularly in the areas of cognitive radio networks, machine learning, and ICT solutions for societal development. His numerous accolades and impactful publications underscore his standing as a leading researcher in his field, and his continued contributions promise further advancements in the intersection of technology and human development.

Jamal Raiyn | Deep Learning | Best Researcher Award

Prof. Dr. Jamal Raiyn | Deep Learning | Best Researcher Award

Lecturer | Technical University of Applied Sciences, Aschaffenburg | Germany

Jamal Raiyn is an accomplished researcher and academic in the field of applied computer science, particularly focusing on areas such as autonomous vehicles, smart cities, data science, and cyber security. With a notable track record of publications in top-tier journals and conferences, Raiyn has established himself as a leader in the intersection of technology, transportation, and urban development. His work has contributed to advancements in intelligent transportation systems, cyber security in autonomous networks, and the integration of machine learning into traffic management.

Profile

Google Scholar

Education

Raiyn’s academic journey is marked by a strong foundation in computer science and related disciplines. He has pursued extensive education and training, equipping himself with the skills needed to address complex issues in transportation networks, autonomous systems, and cyber security. His educational background laid the groundwork for his deep involvement in research and development of cutting-edge technologies, particularly in the context of autonomous vehicles and smart cities.

Experience

Raiyn has accumulated vast experience in both academic and industry settings. Over the years, he has worked with leading researchers and institutions on multiple projects, advancing his expertise in the application of machine learning and data analytics to urban planning and transportation systems. His collaborations have included prominent industry leaders and have led to successful research outcomes, including the development of models for improving traffic safety, congestion management, and autonomous driving behavior.

Research Interests

Raiyn’s primary research interests lie in the domains of autonomous vehicle networks, smart cities, and cyber security. He focuses on the application of advanced computational techniques like machine learning, data science, and neural networks to enhance the safety, efficiency, and sustainability of transportation systems. Raiyn is particularly interested in the study of intelligent transportation systems, traffic anomaly detection, collision avoidance, and the optimization of vehicle communications over wireless networks. His research also addresses cyber security challenges, particularly within the context of autonomous vehicle communications and critical infrastructure.

Awards

Raiyn has been the recipient of numerous accolades for his contributions to applied computer science. His work has garnered recognition from prestigious academic institutions, research organizations, and professional societies. Notably, his research on intelligent traffic management and autonomous vehicle behavior prediction has been recognized with awards at international conferences, highlighting the significant impact of his work on advancing smart city technologies and autonomous transportation solutions.

Publications

Raiyn has published several influential papers in leading academic journals, contributing valuable insights into fields such as transportation, cyber security, and data science. Some of his notable publications include:

Raiyn, J., & Weidl, G. (2025). “Improvement of Collision Avoidance in Cut-In Maneuvers Using Time-to-Collision Metrics.” Smart Cities.

Raiyn, J., Chaar, M. M., & Weidl, G. (2025). “Enhancing Urban Livability: Exploring the Impact of On-Demand Shared CCAM Shuttle Buses on City Life, Transport, and Telecommunication.”

Raiyn, J., & Weidl, G. (2024). “Predicting Autonomous Driving Behavior through Human Factor Considerations in Safety-Critical Events.” Smart Cities, 7(1), 460-474.

Raiyn, J. (2024). “Maritime Cyber-Attacks Detection Based on a Convolutional Neural Network.” Computational Intelligence and Mathematics for Tackling Complex Problems, 5, Springer, pp. 115-122.

Raiyn, J., & Rayan, A. (2023). “Identifying Safety-Critical Events in Data from Naturalistic Driving Studies.” International Journal of Simulation Systems, Science & Technology, 24(1).

Raiyn, J. (2022). “Detection of Road Traffic Anomalies Based on Computational Data Science.” Discover Internet of Things, 2(6).

Raiyn, J. (2022). “Using Dynamic Market-Based Control for Real-Time Intelligent Speed Adaptation Road Networks.” Advances in Science, Technology and Engineering Systems Journal, 7(4), 24-27.

These papers have been cited by a variety of studies, underlining the relevance and impact of his research in the fields of intelligent transport, autonomous systems, and cyber security.

Conclusion

Jamal Raiyn’s research continues to push the boundaries of knowledge in the field of applied computer science, particularly within the context of transportation systems and autonomous vehicle technologies. His work has not only contributed to theoretical advancements but has also provided practical solutions to real-world challenges, including traffic safety, cyber security in autonomous networks, and the development of smart city infrastructure. Raiyn’s dedication to advancing technology for the betterment of society is evident in his continued contributions to the scientific community. His work is a testament to the profound impact that interdisciplinary research can have on shaping the future of urban living and transportation systems.

Yunxiang Lu | Neural Networks | Best Researcher Award

Dr. Yunxiang Lu | Neural Networks | Best Researcher Award

Ph.D | College of Automation & College of Artificial Intelligence | China

Dr. Yunxiang Lu is a dedicated researcher and academic currently affiliated with the College of Automation and the College of Artificial Intelligence at Nanjing University of Posts and Telecommunications, China. His work spans advanced topics in control science, neural networks, and ecological competition networks, underpinned by rigorous academic and practical experiences. Dr. Lu’s career is marked by his pursuit of ground breaking research, particularly in the realms of dynamic systems, network topology, and bifurcation analysis. Through a robust combination of theoretical exploration and simulation-based validation, he has significantly contributed to the field of artificial intelligence and control systems.

Profile

Scopus

Education

Dr. Lu embarked on a combined Master and Ph.D. program in Control Science and Engineering in 2019. As part of his academic journey, he is currently affiliated with the Polish Academy of Sciences – Institute of Systems Research for a year-long research collaboration. This academic foundation has provided him with a strong grasp of theoretical frameworks and hands-on application in control engineering, establishing him as a skilled scholar and innovator in his domain.

Experience

Dr. Lu’s professional experience includes a stint as an IT Technical Engineer at China Telecom Corporation, where he contributed to the 5G+MEC smart factory project, enhancing his expertise in telecommunications and automation. His role involved exploring the integration of 5G technologies in industrial applications, further broadening his technical horizon. Additionally, his active participation in academia includes leading research projects funded by Jiangsu Province, with notable achievements in ecological competition networks and time-delay feedback control mechanisms.

Research Interests

Dr. Lu’s research interests focus on fractional-order systems, neural networks, ecological dynamics, and the control of anomalous diffusion processes. He aims to uncover the intricate behaviors of complex networks influenced by various dynamic parameters. His work explores how time delays, fractional orders, and network topologies impact system stability and evolution, with applications ranging from neural systems to cyber-physical and ecological networks.

Awards and Honors

Dr. Lu has received numerous accolades recognizing his academic excellence and contributions. Notably, he was honored as the Excellent Graduate of Nanjing University of Posts and Telecommunications in 2022 and received the prestigious Postgraduate Academic Scholarship awards multiple times during his tenure. These distinctions underscore his dedication and consistent performance in both research and academics.

Publications

Dr. Lu has co-authored several impactful publications in esteemed journals.

Tipping prediction of a class of large-scale radial-ring neural networks

    • Authors: Lu, Y., Xiao, M., Wu, X., Cao, J., Zheng, W.X.
    • Publication Year: 2025
    • Citations: 0

Complex pattern evolution of a two-dimensional space diffusion model of malware spread

    • Authors: Cheng, H., Xiao, M., Lu, Y., Rutkowski, L., Cao, J.
    • Publication Year: 2024
    • Citations: 0

Spatiotemporal Evolution of Large-Scale Bidirectional Associative Memory Neural Networks With Diffusion and Delays

    • Authors: Lu, Y., Xiao, M., Liang, J., Wang, Z., Cao, J.
    • Publication Year: 2024
    • Citations: 1

Stability and Bifurcation Exploration of Delayed Neural Networks with Radial-Ring Configuration and Bidirectional Coupling

    • Authors: Lu, Y., Xiao, M., He, J., Wang, Z.
    • Publication Year: 2024
    • Citations: 6

Stability and Dynamics Analysis of Time-Delay Fractional-Order Large-Scale Dual-Loop Neural Network Model With Cross-Coupling Structure

    • Authors: Du, X., Xiao, M., Qiu, J., Lu, Y., Cao, J.
    • Publication Year: 2024
    • Citations: 0

QUALITATIVE ANALYSIS OF HIGH-DIMENSIONAL NEURAL NETWORKS WITH THREE-LAYER STRUCTURE AND MULTIPLE DELAYS

    • Authors: He, J., Xiao, M., Lu, Y., Sun, Y., Cao, J.
    • Publication Year: 2024
    • Citations: 0

Early warning of tipping in a chemical model with cross-diffusion via spatiotemporal pattern formation and transition

    • Authors: Lu, Y., Xiao, M., Huang, C., Wang, Z., Cao, J.
    • Publication Year: 2023
    • Citations: 8

Tipping point prediction and mechanism analysis of malware spreading in cyber–physical systems

    • Authors: Xiao, M., Chen, S., Zheng, W.X., Wang, Z., Lu, Y.
    • Publication Year: 2023
    • Citations: 10

Control of tipping in a small-world network model via a novel dynamic delayed feedback scheme

    • Authors: He, H., Xiao, M., Lu, Y., Wang, Z., Tao, B.
    • Publication Year: 2023
    • Citations: 9

Bifurcation Dynamics Analysis of A Class of Fractional Neural Networks with Mixed Delays

    • Authors: Luan, Y., Lu, Y., Xiao, M., Zhang, J.
    • Publication Year: 2023
    • Citations: 0

Conclusion

Dr. Yunxiang Lu exemplifies the synthesis of academic brilliance, practical expertise, and research acumen. His dedication to advancing knowledge in control systems and artificial intelligence positions him as a visionary scholar in his field. Through his continued exploration of dynamic networks and innovative control strategies, he remains committed to addressing complex challenges in modern science and technology.