Oluwatobi Adedamola Ayilara-Adewale | Artificial Intelligence | Editorial Board Member

Published on by World Top Scientists

Dr. Oluwatobi Adedamola Ayilara-Adewale | Artificial Intelligence | Editorial Board Member

Lecturer | Osun State University | Nigeria

Dr. Oluwatobi Adedamola Ayilara-Adewale is a computer science researcher specializing in machine learning, AI-driven cybersecurity and intelligent systems, serving as an academic and research contributor in these domains. With advanced degrees in computer science and a strong foundation in computational methods and digital systems, he has gained professional experience through participation in national and international research projects involving digital resilience, smart agriculture, climate-focused data analytics and secure digital infrastructures, often providing technical leadership in multidisciplinary teams. His research focuses on artificial intelligence, IoT security, intrusion detection, blockchain security, predictive analytics and cyber-resilient architectures, supported by numerous peer-reviewed publications spanning journals, conference outputs and book chapters. He has contributed to the development of machine learning models for security, intelligent decision-support systems and emerging frameworks for digital trust. Dr. Ayilara-Adewale has received recognition for innovative research and holds professional certifications in cloud computing, cybersecurity and penetration testing. He is an active member of multiple professional bodies, reflecting his commitment to advancing knowledge in computing and cybersecurity, and he has engaged in collaborative initiatives that strengthen the ecosystem of applied AI research. His growing scholarly profile, technical versatility and dedication to secure and intelligent systems position him as a valuable contributor to contemporary research and a strong candidate for excellence awards.

Profiles: Google Scholar

Featured Publications

1. Jimoh, K., Ajayi, A., & Ayilara, O. (2014). Intelligent model for manual sorting of plastic wastes. International Journal of Computer Applications, 101(7), 20–26.

2. Jimoh, K. O., Adepoju, T. M., Sobowale, A. A., & Ayilara, O. A. (2018). Offline gesture recognition system for Yorùbá numeral counting. Asian Journal of Research in Computer Science, 1(4), 1–11.

3. Ajayi, A. O., Jimoh, K. A., & Ayilara, O. A. (2016). Evaluation of plastic waste classification systems. British Journal of Mathematics & Computer Science, 16(3), 1–11.

4. Ayilara, M. S., Fasusi, S. A., Ajakwe, S. O., Akinola, S. A., Ayilara-Adewale, O. A., … (2025). Impact of climate change on agricultural ecosystem. In Climate change, food security, and land management: Strategies for a sustainable future.

5. Olanrewaju, A., & Ayilara, O. A. (2024). The effect of data compromises on internet users: A review on financial implication of the elderly in the United States. African Journal of Social Sciences and Humanities Research, 1, 28–37.

Dr. Oluwatobi Adedamola Ayilara-Adewale’s work advances secure and intelligent digital ecosystems by integrating artificial intelligence with resilient cybersecurity frameworks. His research contributes to safer technologies, sustainable data-driven solutions and innovative systems that support societal development, industry transformation and global digital trust.

Oluwatobi Adedamola Ayilara-Adewale | Artificial Intelligence | Innovative Research Award

Published on by World Top Scientists

Dr. Oluwatobi Adedamola Ayilara-Adewale | Artificial Intelligence | Innovative Research Award

Lecturer | Osun State University | Nigeria

Dr. Oluwatobi Adedamola Ayilara-Adewale is a computer science researcher specializing in machine learning, AI-driven cybersecurity and intelligent systems, serving as an academic and research contributor in these domains. With advanced degrees in computer science and a strong foundation in computational methods and digital systems, he has gained professional experience through participation in national and international research projects involving digital resilience, smart agriculture, climate-focused data analytics and secure digital infrastructures, often providing technical leadership in multidisciplinary teams. His research focuses on artificial intelligence, IoT security, intrusion detection, blockchain security, predictive analytics and cyber-resilient architectures, supported by numerous peer-reviewed publications spanning journals, conference outputs and book chapters. He has contributed to the development of machine learning models for security, intelligent decision-support systems and emerging frameworks for digital trust. Dr. Ayilara-Adewale has received recognition for innovative research and holds professional certifications in cloud computing, cybersecurity and penetration testing. He is an active member of multiple professional bodies, reflecting his commitment to advancing knowledge in computing and cybersecurity, and he has engaged in collaborative initiatives that strengthen the ecosystem of applied AI research. His growing scholarly profile, technical versatility and dedication to secure and intelligent systems position him as a valuable contributor to contemporary research and a strong candidate for excellence awards.

Profiles: Google Scholar

Featured Publications

1. Jimoh, K., Ajayi, A., & Ayilara, O. (2014). Intelligent model for manual sorting of plastic wastes. International Journal of Computer Applications, 101(7), 20–26.

2. Jimoh, K. O., Adepoju, T. M., Sobowale, A. A., & Ayilara, O. A. (2018). Offline gesture recognition system for Yorùbá numeral counting. Asian Journal of Research in Computer Science, 1(4), 1–11.

3. Ajayi, A. O., Jimoh, K. A., & Ayilara, O. A. (2016). Evaluation of plastic waste classification systems. British Journal of Mathematics & Computer Science, 16(3), 1–11.

4. Ayilara, M. S., Fasusi, S. A., Ajakwe, S. O., Akinola, S. A., Ayilara-Adewale, O. A., … (2025). Impact of climate change on agricultural ecosystem. In Climate change, food security, and land management: Strategies for a sustainable future.

5. Olanrewaju, A., & Ayilara, O. A. (2024). The effect of data compromises on internet users: A review on financial implication of the elderly in the United States. African Journal of Social Sciences and Humanities Research, 1, 28–37.

Dr. Oluwatobi Adedamola Ayilara-Adewale’s work advances secure and intelligent digital ecosystems by integrating artificial intelligence with resilient cybersecurity frameworks. His research contributes to safer technologies, sustainable data-driven solutions and innovative systems that support societal development, industry transformation and global digital trust.

María Inmaculada Mohino-Herranz | Artificial Intelligence| Best Research Article Award

Published on by World Top Scientists

Dr. María Inmaculada Mohino-Herranz | Artificial Intelligence| Best Research Article Award

Investigador, INTA, Spain

Inmaculada Mohíno Herranz is a distinguished researcher in the fields of signal processing, pattern recognition, and emotion detection. She currently works at the National Institute of Aerospace Technology (INTA), bringing her extensive expertise in physiological signal analysis to the forefront of innovative research. 🌟 Her career reflects a commitment to advancing technology and science, contributing to both academia and industry.

Publication profile

Scopus

Education

Inmaculada holds an impressive academic background, beginning with her M.Eng. in Telecommunication Engineering (2010), followed by a second degree in Electronics Engineering (2012), and a Master’s degree in Information and Communication Technologies (2015). 📚 She culminated her academic journey with a Ph.D. in Information and Communication Technologies (2017, with honors) from the University of Alcalá, Madrid, Spain. 🎓

Experience

She has built a solid career in academia and research, having worked at the Signal Theory and Communications Department of the University of Alcalá, where she was part of the Applied Signal Processing research group until 2021. 📡 Currently, she continues her research at INTA, contributing to projects related to aerospace technology. She has also been actively involved in supervising final degree and master’s projects, shaping future innovators. 👩‍🏫

Research Focus

Inmaculada’s research revolves around physiological signal processing, pattern recognition, emotion recognition, and stress detection. 💡 Her work is especially significant in understanding how physiological data can be used to monitor emotional states, which has applications ranging from healthcare to technology-enhanced well-being. 💻

Awards and Honors

Inmaculada has received recognition for her outstanding contributions to the field of Information and Communication Technologies, including supervising several successful degree projects and participating in numerous public and private-funded research initiatives. 🏆 Her efforts in academic and industrial projects further solidify her reputation as a leading researcher.

Publication Top Notes

Inmaculada Mohíno Herranz has authored various impactful papers. She has published nine journal papers, six of which are indexed in the Journal Citation Report. 📄 She has also written a book chapter and around 20 conference papers, showcasing her active engagement in research dissemination.

Metrological analysis on measuring techniques used to determine solubility of solids in supercritical carbon dioxide – Published in Measurement: Journal of the International Measurement Confederation (2025), this article has no citations yet.

Initializing the weights of a multilayer perceptron for activity and emotion recognition – Published in Expert Systems with Applications (2024), this article has no citations yet.

Introducing the ReaLISED Dataset for Sound Event Classification – Published in Electronics (2022), cited by two articles.

Linear detector and neural networks in cascade for voice activity detection in hearing aids – Published in Applied Acoustics (2021), cited by one article.

A wrapper feature selection algorithm: An emotional assessment using physiological recordings from wearable sensors – Published in Sensors (2020), this open-access article focuses on emotion assessment using physiological data from wearable sensors.