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.

JUN WON HO | Computer Engineering | Best Researcher Award

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Dr. JUN WON HO | Computer Engineering | Best Researcher Award

Research Fellow at Incheon National University, South Korea.

Dr. Jun Won-Ho 🎓 is a dedicated Research Fellow at Incheon National University, South Korea 🇰🇷. He earned his Ph.D. in Computer Engineering in February 2023 🧠, focusing on sleep pattern analysis in an unconscious, non-intrusive state 🛏️. His innovations aim to revolutionize sleep health through biosensor-based technologies 💡. With peer-reviewed publications in SCI-indexed journals 📚 and a patent on body weight estimation while lying in bed 🧾, Dr. Jun is making sleep monitoring accessible and home-based. His work bridges healthcare and engineering, offering practical solutions for sleep apnea detection 🩺 using biosensors and ambient signals 🌐.

Professional Profile:

ORCID

Suitability for Best Researcher Award – Dr. Jun Won-Ho

Dr. Jun Won-Ho is highly suitable for the Best Researcher Award due to his pioneering research at the intersection of biomedical engineering and computer science. Despite being an early-career researcher, he has demonstrated remarkable innovation and scientific productivity, especially in the field of non-intrusive sleep health monitoring. His Ph.D. and postdoctoral work have resulted in SCI-indexed journal publications, a granted patent, and the development of AI-based, contact-free technologies to address global health concerns like sleep apnea—showing both originality and real-world impact.

🎓 Education and Experience

  • 🎓 Ph.D. in Computer Engineering – Incheon National University (2023)

  • 🧪 Research Fellow – Incheon National University (Current)

  • 📄 Published in SCI-indexed journals – Including Sensors

  • 🛏️ Doctoral Research – Focused on unobtrusive sleep pattern analysis

  • 🔬 Ongoing Research – Development of self-screening technology for sleep apnea

  • 🧾 Patent Holder – System for estimating body weight while lying on a bed

🚀 Professional Development

Dr. Jun Won-Ho has significantly contributed to the field of sleep science and biomedical engineering 🧠. His journey began with a strong academic foundation in computer engineering 🎓, which he has transformed into impactful research focused on real-world health challenges 🩺. He has authored articles in SCI-indexed journals 📚 and currently works on a cutting-edge sleep apnea screening solution using biosensors and environmental data 🌙📊. His patented invention 🧾 and active engagement in non-contact health monitoring technologies reflect his innovative mindset and commitment to improving global health accessibility 🌍💡.

🧬 Research Focus Category

Dr. Jun Won-Ho’s research falls under the category of Biomedical Engineering and Sleep Science 🧠🛌. He is especially focused on unobtrusive health monitoring, developing systems that use biosensors, physiological signals, and environmental data to analyze sleep patterns and detect sleep disorders like apnea 😴🩺. His goal is to eliminate the need for intrusive clinical testing such as polysomnography 🧪 and instead offer home-based, AI-powered health solutions 🌐📲. His patented work on weight estimation during sleep complements his broader mission of advancing digital health technologies for continuous, contact-free care 🧾💡.

🏅 Awards and Honors

  • 🧾 Patent Granted – System for Estimating Body Weight While Lying on a Bed (KR 10-2556030)

  • 📄 SCI-Indexed Publications – Published 2 articles in renowned journals like Sensors

  • 📌 Ph.D. Achievement – Doctorate completed with impactful research in 2023

  • 🏆 Nominated for Best Researcher Award – For contributions to biomedical sleep technology

  • 🧠 Research Innovation Recognition – Development of non-contact sleep apnea screening system

Publication Top Notes

1. Detection of Sleep Posture via Humidity Fluctuation Analysis in a Sensor-Embedded Pillow

  • Published: April 30, 2025

  • Journal: Bioengineering

  • DOI: 10.3390/bioengineering12050480

  • Summary: This study introduces a novel method for detecting sleep posture by analyzing humidity fluctuations using sensors embedded in a pillow. The system monitors changes caused by respiration and perspiration, offering a non-invasive approach to sleep posture detection.

2. Sleep Pattern Analysis in Unconstrained and Unconscious State

  • Published: November 29, 2022

  • Journal: Sensors

  • DOI: 10.3390/s22239296

  • Citation Count: 6

  • Summary: This research analyzes sleep patterns in individuals without physical constraints or active awareness. Utilizing various sensors, the study collects physiological and environmental data to classify sleep stages, providing insights into natural sleep behaviors.MDPI

3. Multi-Sensor Data Fusion with a Reconfigurable Module and Its Application to Unmanned Storage Boxes

  • Published: July 19, 2022

  • Journal: Sensors

  • DOI: 10.3390/s22145388

  • Citation Count: 12

  • Summary: This paper presents a reconfigurable module for multi-sensor data fusion, applied to unmanned storage boxes. By integrating data from various sensors, the system enhances reliability and security in automated storage environments.

Conclusion

Dr. Jun Won-Ho exemplifies the qualities of a Best Researcher Award recipient through his innovative mindset, impactful biomedical applications, and commitment to global health technology advancement. His work is not only academically rigorous but also practically transformative, making essential health monitoring more accessible, affordable, and patient-friendly. He stands out as a rising star in biomedical engineering, well-deserving of this prestigious recognition.