Pengfei Wei | Computer Science | Best Researcher Award

Dr. Pengfei Wei | Computer Science | Best Researcher Award 

Senior Engineer at Guangdong University of Technology | China

Dr. Pengfei Wei is a Senior Engineer at Guangdong University of Technology, recognized for his pioneering contributions to the field of computer science, particularly in multimodal learning, knowledge tracing, edge artificial intelligence, and task-oriented dialogue systems. He holds a Ph.D. in Computer Science, where his research focused on integrating deep learning models with practical applications in intelligent education and human–machine interaction. Combining academic rigor with industrial innovation, he brings substantial experience from both enterprise research and academic development, bridging the gap between theory and real-world technology deployment. His work encompasses advanced methods such as visual-enhanced transformers for multimodal named entity recognition, genetic-inspired relation extraction, and the introduction of Kolmogorov–Arnold representations in knowledge tracing, which have improved model interpretability and performance in AI-based learning systems. In addition to his theoretical advancements, he has successfully led projects on real-time lab-safety analytics and large-scale AI deployment using Huawei Ascend, Nvidia, and TPU platforms, contributing to the broader industrial adoption of edge AI technologies. Dr. Pengfei Wei has authored numerous peer-reviewed papers in top-tier international journals and conferences, including Neural Networks, ICMR, and IJCAI, and serves as a reviewer for several prestigious publications such as Neural Networks, Pattern Recognition Letters, AAAI, and IJCNN. His collaborative initiatives with research teams and institutions have fostered multidisciplinary innovation, emphasizing the integration of AI with blockchain, big data, and education systems. A dedicated mentor and research leader, he actively supports student-led research and fosters the development of next-generation AI scholars. His professional memberships with the China Computer Federation (CCF) and the Association for Computing Machinery (ACM) reflect his strong engagement in the global computing community. Dr. Pengfei Wei’s research continues to push the boundaries of multimodal understanding and intelligent systems, driving transformative progress in computational learning and applied artificial intelligence. Through his sustained contributions, he remains committed to advancing the capabilities of intelligent technologies that enhance human productivity, knowledge discovery, and digital transformation.

Featured Publications:

  • Liao, W., B. Zeng, Yin, X., & Wei, P. (2021). An improved aspect-category sentiment analysis model for text sentiment analysis based on RoBERTa. Applied Intelligence, 51(6), 3522–3533.

  • Liao, W., Zeng, B., Liu, J., Wei, P., Cheng, X., & Zhang, W. (2021). Multi-level graph neural network for text sentiment analysis. Computers & Electrical Engineering, 92, 107096.

  • Liao, W., Zeng, B., Liu, J., Wei, P., & Fang, J. (2022). Image-text interaction graph neural network for image-text sentiment analysis. Applied Intelligence, 52(10), 11184–11198.

  • Liao, W., Zeng, B., Liu, J., Wei, P., & Cheng, X. (2022). Taxi demand forecasting based on the temporal multimodal information fusion graph neural network. Applied Intelligence, 52(10), 12077–12090.

  • Wei, P., Zeng, B., & Liao, W. (2022). Joint intent detection and slot filling with wheel-graph attention networks. Journal of Intelligent & Fuzzy Systems, 42(3), 2409–2420.

  • Wei, P., Ouyang, H., Hu, Q., Zeng, B., Feng, G., & Wen, Q. (2024). VEC-MNER: Hybrid transformer with visual-enhanced cross-modal multi-level interaction for multimodal NER. Proceedings of the International Conference on Multimedia Retrieval (ICMR 2024).

  • Wen, S., Zeng, B., Liao, W., Wei, P., & Pan, Z. (2021). Research and design of credit risk assessment system based on big data and machine learning. Proceedings of the IEEE 6th International Conference on Big Data Analytics (ICBDA 2021), 9–13.

Oluwafemi Oke | Cybersecurity | Best Researcher Award

Dr. Oluwafemi Oke | Cybersecurity | Best Researcher Award

Lecturer at Near East University, Cyprus.

Oluwafemi Ayotunde Oke is a passionate researcher and lecturer specializing in Artificial Intelligence (AI), Machine Learning (ML), and Cybersecurity. He holds a Ph.D. in Computer Information Systems from Near East University and has extensive experience in software development, IT engineering, and research assistance. His research focuses on AI-driven innovations in cardiology, finance, and healthcare. With numerous publications in high-impact journals, Oluwafemi actively contributes to international conferences, presenting groundbreaking insights. He is also a member of the Computer Information Systems Research and Technology Centre and has been nominated for prestigious research awards. ✨📊

Professional Profile:

ORCID Profile

Suitability for Best Researcher Award 🏆

Dr. Oluwafemi Ayotunde Oke is highly suitable for the Best Researcher Award due to his outstanding contributions to Artificial Intelligence (AI), Machine Learning (ML), and Cybersecurity. His research spans across multiple domains, including healthcare, finance, and smart cities, demonstrating the interdisciplinary impact of his work.

Education & Experience 🎓💼

📌 Ph.D. in Computer Information Systems – Near East University (2024)
📌 M.Sc. in Software Engineering – Babcock University (2020)
📌 B.Sc. in Computer Engineering (Technology) – Babcock University (2016)

👨‍🏫 Part-Time Lecturer – Near East University (2023-Present)
🔬 Research Assistant – Near East University (2022-Present)
🌍 Assistant Director of IT & Communications – National Association of Nigerian Students (2022-2024)
💻 IT Engineer – GIFA INC (2021)
🖥️ IT Developer – Yeni Bakis (2021)
🔧 Design Engineer – Daxlinks Global (2021)
📚 Graduate Research Assistant – Computer Professionals of Nigeria (2020)
🎧 Head of Audiovisuals – Taidob College (2018-2019)

Professional Development 🚀📚

Oluwafemi Oke continuously hones his expertise through global certifications and specialized training in AI, cybersecurity, and IT. He holds IBM certifications in AI, Machine Learning, and Cybersecurity 🏅 and has completed courses from Duke University and Yale University on Cybersecurity and Well-being. As a Huawei Certified Network Associate (HCIA), he has gained expertise in Big Data, Cloud Computing, and AI Security. His Android Developer and CompTIA certifications further strengthen his software engineering skills. Committed to academic growth, he actively engages in research memberships, workshops, and technology conferences, ensuring he stays ahead in the ever-evolving tech landscape. 🔍💡

Research Focus 🔬📊

Oluwafemi Oke’s research is centered around Artificial Intelligence (AI) and its transformative impact on various fields. His work in Natural Language Processing (NLP), Electrocardiogram (ECG) image classification, and AI-driven financial services showcases the power of AI in improving healthcare, finance, and education. 💙🧠 He has conducted bibliometric studies on AI in financial services, examined AI’s role in cardiology, and explored machine learning in conversational systems. 🌍📈 His research also extends to AI’s role in smart cities, IoT-based water management, and climate change predictions. Through innovative AI solutions, he aims to revolutionize healthcare, security, and financial technologies. 🤖💰

Awards & Honors 🏆🎖️

🏅 International Research Awards on Cybersecurity and Cryptography (Nominee, ID 1896)
📜 2024 Best Ph.D. Thesis Award – Electronics Journal
🎓 Member, Computer Information Systems Research and Technology Centre
🏆 Multiple Research Publications in SSCI/SCI-Expanded Journals
🌍 Presenter at Prestigious International Conferences

Publication Top Notes

  1. Building Tomorrow Green and Sustainable Imperatives in Smart City Development (2025) | Book Chapter
    📌 Authors: Oluwafemi Ayotunde Oke, Nuriye Sancar, Nadire Cavus
    📌 DOI: 10.1007/978-3-031-72479-4_38

  2. A Systematic Review on the Impact of Artificial Intelligence on Electrocardiograms in Cardiology (2025-03) | Journal Article
    📌 Authors: Oluwafemi Ayotunde Oke, Nadire Cavus
    📌 Journal: International Journal of Medical Informatics
    📌 DOI: 10.1016/j.ijmedinf.2024.105753

  3. Artificial Intelligence for Computer Vision: Bibliometric Analysis (2024-03) | Preprint
    📌 Authors: Oke O, Cavus N
    📌 DOI: 10.21203/rs.3.rs-4098674/v1

  4. The Role of AI in Financial Services: A Bibliometric Analysis (2024-01-19) | Journal Article
    📌 Authors: Oluwafemi Ayotunde Oke, Nadire Cavus
    📌 Journal: Journal of Computer Information Systems
    📌 DOI: 10.1080/08874417.2024.2304545

  5. The Impact of Artificial Intelligence in Foreign Language Learning Using Learning Management Systems: A Systematic Literature Review (2023-06-30) | Journal Article
    📌 Authors: Оке Олувафемі Айотунде, Дашти Ісміль Джаміль, Надір Кавус
    📌 Journal: Information Technologies and Learning Tools
    📌 DOI: 10.33407/itlt.v95i3.5233