Pengfei Wei | Computer Science | Best Researcher Award

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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.

Profile: Orcid | Google Scholar

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.

Rashid Hussain | Fuzzy Mathematics | Best Researcher Award

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Mr. Rashid Hussain | Fuzzy Mathematics | Best Researcher Award

PhD Student at Karakoram International University, Pakistan.

Rashid Hussain is a dedicated mathematician and academic specializing in Fuzzy Mathematics 🤖📊. He is currently pursuing a Ph.D. in Mathematics at COMSATS University Islamabad, Wah Campus 🎓. With a strong background in mathematical modeling and decision-making applications, he has contributed to various international journals 📚. Rashid has been a visiting lecturer at multiple institutions, including Karakoram International University, Fatima Jinnah Degree College for Women, and Sarhad University of Science and Information Technology 🏫. His research focuses on Pythagorean fuzzy sets, decision-making algorithms, and artificial intelligence applications 🧠🔢.

Professional Profile

Scopus Profile

Education 🎓

✅ Ph.D. in Mathematics (Fuzzy Mathematics) – COMSATS University Islamabad (In Process)
✅ MS/MPhil in Mathematics – Karakoram International University, Gilgit (2018-2020)
✅ BS in Mathematics – Karakoram International University, Gilgit (2013-2017)
✅ B.Ed (Science Education) – Allama Iqbal Open University, Islamabad (2021)
✅ F.Sc (Pre-Engineering) – Public School and College, Jutial Gilgit (2011)
✅ SSC (Science) – Public School and College, Jutial Gilgit (2009)

Work Experience 👨‍🏫

📌 Visiting Teaching Associate – Karakoram International University, Gilgit (March 2017 – Aug 2017)
📌 Visiting Lecturer – Karakoram International University, Gilgit (Oct 2020 – Present)
📌 Visiting Lecturer – Fatima Jinnah Degree College for Women (Oct 2022 – Feb 2023)
📌 Visiting Lecturer – Sarhad University of Science & IT, Peshawar (Oct 2021 – Present)

Professional Development 📖

Rashid Hussain has actively engaged in various professional training and skill-building programs 🎯. He has completed courses in Machine Learning, Practical English Skills, and a 14-day English Language Fluency Course to enhance his communication abilities 📢. His academic contributions extend beyond teaching, with multiple research publications in leading mathematical and decision-making journals 📑. He has also authored books on Linear Algebra, Circles, and Absolute Value Equations 📚. Through continuous learning and research, he aims to develop innovative mathematical models for solving real-world problems in fuzzy logic and artificial intelligence 🤖🔢.

Research Focus 🔬

Rashid Hussain’s research revolves around Fuzzy Mathematics and its Applications 🧮. His primary focus is on Pythagorean fuzzy sets, similarity measures, multi-criteria decision-making, and artificial intelligence integration 🤖📊. He has contributed significantly to pattern recognition, clustering algorithms, and optimization techniques used in engineering, medical diagnosis, and machine learning 🏥📡. His recent work includes novel distance and similarity measures for fuzzy set analysis, contributing to advancements in decision-making systems and computational intelligence 🤓💡. His research is paving the way for efficient and intelligent mathematical models used in various industries worldwide 🌍📈.

Awards & Honors 🏆

🏅 Published extensively in high-impact journals 📖
🏅 Significant contributions to Fuzzy Mathematics research 🔢
🏅 Recognized for outstanding teaching and research contributions 👨‍🏫
🏅 Authored books on mathematical topics 📚
🏅 Actively involved in international research collaborations 🌎

Publication Top notes

Authors: R. Hussain, Z. Hussain, N.M. Sarhan, N. Juraev, S. Ur Rahman
Year: 2024