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

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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.

Huxiong Li | Artificial Intelligence | Artificial Intelligence

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Prof. Dr. Huxiong Li | Artificial Intelligence | Artificial Intelligence

Professor | Shaoxing University | China

Prof. Dr. Huxiong Li is a leading researcher in artificial intelligence, specializing in 3D vision, intelligent perception, urban digital twins, and complex network control. He has made significant contributions through innovative research, demonstrated by his extensive publications, patents, and leadership of multiple national and international projects. His work bridges AI technologies with practical applications in cultural heritage preservation and smart city infrastructure, reflecting a strong interdisciplinary approach. Over the years, he has fostered collaborations with global institutions, enhancing the reach and impact of his research. Prof. Li’s guidance of numerous projects has not only advanced scientific understanding but also facilitated industrial implementation of AI technologies. His research demonstrates consistent excellence, originality, and societal relevance, positioning him as a prominent figure in geospatial artificial intelligence. According to Scopus, his measurable research impact includes 28 citations, 9 documents, and an h-index of 402.

Profiles: Scopus | ORCID

Featured Publications

1. Reducing the clustering challenge in the IoT using two disjoint convex hulls. Scientific Reports, 2025.

2. Integrating InSAR coherence and air pollution detection satellites to study the impact of war on air quality. International Journal of Applied Earth Observation and Geoinformation, 2025.

 

Álvaro Figueira | Artificial Intelligence | Best Paper Award

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Assist. Prof. Dr. Álvaro Figueira | Artificial Intelligence | Best Paper Award

Professor Auxiliar, FCUP – Universidade do Porto, Portugal

Profile

Orcid

Álvaro Figueira is a distinguished academic and researcher in the field of Computer Science, currently serving as a Professor (Prof. Auxiliar) at Universidade do Porto, Faculdade de Ciências in Portugal. With a robust academic background and extensive experience, his research focuses on data mining, machine learning, social network analysis, and eLearning. Figueira’s passion for technology and innovation is evident in his contribution to various scientific fields, including data visualization and text mining, where his work aims to bridge theory with practical applications. With years of experience in teaching and leading research initiatives, Figueira is a prominent figure in his discipline. 📚💻

Education

Álvaro Figueira’s academic journey is distinguished by his advanced qualifications in Computer Science. He obtained his Bachelor’s (BSc) degree from Universidade do Porto, followed by a Master’s (MSc) from Imperial College London. He continued his academic excellence by completing a Ph.D. at Universidade do Porto in 2004, where he focused on Computer Science. Additionally, Figueira pursued Post-Graduation in Business Intelligence and Analytics at Porto Business School in 2017, further enhancing his expertise. 🎓📖

Experience

Throughout his career, Álvaro Figueira has amassed a wealth of academic and professional experience. He is currently a Professor at Universidade do Porto, where he teaches and supervises students in the field of Computer Science. He has also worked on a variety of research projects related to eLearning, data science, and machine learning, particularly focused on how these technologies can improve education and business practices. His previous experience includes a prestigious Master’s thesis position at Imperial College London. 🌍📊

Research Interests

Álvaro Figueira’s research interests span a wide array of cutting-edge fields within Computer Science. His primary focus areas include Data Mining, Text Mining, Machine Learning, Social Network Analysis, Data Visualization, and eLearning. Figueira’s work aims to apply computational techniques to improve the analysis of large datasets, making significant strides in understanding and enhancing social networks and educational systems. His research has contributed to the advancement of automated assessment systems and the optimization of learning processes. 📈🔍

Award

Álvaro Figueira’s contributions to computer science and education have been recognized with various awards and accolades. Notably, his research has been funded by several prestigious grants, including those from the Fundação para a Ciência e Tecnologia I.P. and Instituto de Engenharia de Sistemas e Computadores. His excellence in research is further highlighted by his numerous publications in top-tier journals, where he continues to make an impact in the fields of data science and machine learning. 🏆🎖️

Publications Top Notes

Álvaro Figueira’s publication record reflects his significant contributions to the fields of data science, machine learning, and eLearning. Some of his recent publications include:

“Topic Extraction: BERTopic’s Insight into the 117th Congress’s Twitterverse” – Informatics (2024).

“Clustering source code from automated assessment of programming assignments” – International Journal of Data Science and Analytics (2024).

“Comparing Semantic Graph Representations of Source Code: The Case of Automatic Feedback on Programming Assignments” – Computer Science and Information Systems (2024).

“GANs in the Panorama of Synthetic Data Generation Methods” – ACM Transactions on Multimedia Computing, Communications, and Applications (2024).

“On the Quality of Synthetic Generated Tabular Data” – Mathematics (2023).

“Bibliometric Analysis of Automated Assessment in Programming Education: A Deeper Insight into Feedback” – Electronics (2023).