Nafiz Fahad | Computer Science | Best Researcher Award

Published on by Forensic Scientist

Mr. Nafiz Fahad | Computer Science | Best Researcher Award

Multimedia University | Malaysia

Mr. Nafiz Fahad is an emerging AI researcher at Multimedia University, Cyberjaya, Malaysia, recognized for his growing contributions to artificial intelligence in healthcare, computer vision, and natural language processing. His research focuses extensively on explainable AI, clinical decision support systems, and data-driven healthcare intelligence. According to Scopus, he has 19 indexed publications, 122 citations, and an h-index of 6, reflecting the influence and visibility of his scholarly work within the global research community. His scientific output spans chronic disease prediction, dementia analytics, lung disease classification, hypertension ontology development, wound-image segmentation, obesity prediction, and precision public health. These studies incorporate techniques such as deep learning, transfer learning, ensemble learning, hybrid architectures, and explainable machine learning to advance diagnostic accuracy and interpretability in medical AI systems. Beyond health-focused research, Fahad has also contributed high-impact work in fake news detection, generative AI, machine learning security, student performance prediction, agricultural disease detection, vision transformers for physics data, and federated learning enhanced with homomorphic encryption. His ongoing research extends to mental health analytics, EEG decoding models, diabetic retinopathy detection, and agentic AI solutions for healthcare innovation. Fahad’s growing academic recognition includes research awards, best paper achievements, and contributions to high-impact journals and conferences. His multidisciplinary scholarship positions him as a promising young researcher advancing applied AI at the intersection of healthcare, societal well-being, and intelligent systems.

Profiles: Scopus | Google Scholar | LinkedIn

Featured Publications

1. Ahmed, Z., Shanto, S. S., Rime, M. H. K., Morol, M. K., Fahad, N., Hossen, M. J., … (2024). The generative AI landscape in education: Mapping the terrain of opportunities, challenges and student perception. IEEE Access.

2. Mahamud, E., Fahad, N., Assaduzzaman, M., Zain, S. M., Goh, K. O. M., & Morol, M. K. (2024). An explainable artificial intelligence model for multiple lung diseases classification from chest X-ray images using fine-tuned transfer learning. Decision Analytics Journal, 12, 100499.

3. Ahmed, R., Fahad, N., Miah, M. S. U., Hossen, M. J., Morol, M. K., Mahmud, M., … (2024). A novel integrated logistic regression model enhanced with recursive feature elimination and explainable artificial intelligence for dementia prediction. Healthcare Analytics, 6, 100362.

4. Fahad, N., Goh, K. M., Hossen, M. I., Shopnil, K. M. S., Mitu, I. J., Alif, M. A. H., & Tee, C. (2023). Stand up against bad intended news: An approach to detect fake news using machine learning. Emerging Science Journal, 7(4), 1247–1259.

5. Hossain, M. N., Fahad, N., Ahmed, R., Sen, A., Al Huda, M. S., & Hossen, M. I. (2024). Preventing student’s mental health problems with the help of data mining. International Journal of Computing, 23(1), 101–108.

Jiajie Gao | Computer Science | Best Researcher Award

Published on by Forensic Scientist

Mr. Jiajie Gao | Computer Science | Best Researcher Award

Hebei University of Architecture | China

Gao Jiajie is a highly driven and innovative researcher currently pursuing a master’s degree at Hebei University of Architecture. In just two years, he has demonstrated exceptional research prowess by independently publishing three SCI Q3 journal articles, authoring 16 software patents, and leading a national-level project. His commitment to bridging theoretical AI innovations with real-world applications places him at the forefront of emerging research talent in occupational safety and intelligent detection systems.

Professional profile👤

Scopus

Strengths for the Awards✨

Gao Jiajie demonstrates exceptional research performance, particularly notable given his status as a master’s student. His achievements include publishing three SCI Q3 journal articles, securing 16 authorized software patents, and acting as principal investigator on a national-level project—a feat typically rare at this early career stage. His research focuses on applied artificial intelligence in safety-critical systems, such as railway worker compliance, power grid integrity, and smart retail. Gao’s innovation in improving YOLOv5-based detection systems—including integrating CBAM and MPDIoU modules—shows deep technical insight and a solutions-oriented mindset. Moreover, his ability to translate research into real-world industrial collaborations speaks to his applied impact, with outputs in railway safety, insulator fault detection, and retail inventory management. His role as a reviewer for a peer-reviewed journal further highlights his growing reputation in the academic community. 🔍

🎓 Education

Gao Jiajie is presently a master’s student at Hebei University of Architecture, where he is actively involved in cutting-edge research in artificial intelligence and its applications in safety systems. His academic journey is marked by a strong focus on practical innovations and scholarly contributions, showcasing an excellent balance between theory and implementation.

💼 Experience

In his short academic career, Gao Jiajie has already led one national-level project as the principal investigator and served as a key contributor in multiple collaborative initiatives. His leadership resulted in eight authorized software patents and several AI-based detection systems. He also actively participates in academic review processes as a reviewer for the Journal of Electronic Imaging (JEI).

🧠 Research Interest On Computer Science

Gao’s research centers on Artificial Intelligence, particularly in the development of advanced detection algorithms that enhance occupational safety and industrial automation. His innovative approach integrates attention mechanisms (CBAM), improved loss functions (MPDIoU), and real-time object detection models (YOLOv5/YOLOv8), delivering significant accuracy improvements in challenging environments such as railways, power grids, and retail sectors.

🏅 Awards

While still early in his academic journey, Gao Jiajie’s work has garnered national recognition. His role as Principal Investigator of a national-level project, along with his multiple patents and peer-reviewed publications, highlight his merit for the Best Researcher Award. His work stands as a testament to innovation, application, and academic excellence. 🏆

📚 Publications

Gao Jiajie has published three peer-reviewed SCI Q3 journal articles, each making notable contributions to AI-based visual detection systems:

  1. Gao, Jiajie, et al. Safety equipment compliance analysis for occupational safety, Signal, Image and Video Processing, Vol. 19, Article 720, 2025.
    📈 Cited by: Article recently published; citation data forthcoming.

  2. Gao, Jiajie, et al. Enhanced YOLOv8 for high-precision retail cabinet product recognition, Signal, Image and Video Processing, Vol. 19.7, 2025.
    📈 Cited by: 2 articles.

  3. Gao, Jiajie, et al. Research on the algorithm of detecting insulators in high-voltage transmission lines using UAV images, Signal, Image and Video Processing, Vol. 18, Suppl 1, 2024.
    📈 Cited by: 5 articles.

These publications emphasize Gao’s skill in applying deep learning techniques to complex detection challenges in infrastructure and retail environments.

✅ Conclusion

Gao Jiajie exemplifies the qualities of a forward-thinking researcher, blending deep technical knowledge with practical implementation in AI-based safety systems. His rapid output of publications, patents, and leadership in a national project underscores a rare level of maturity, innovation, and commitment at an early academic stage. With outstanding contributions in detection algorithm design, academic reviewing, and cross-sector collaboration, Gao is a deserving nominee for the Best Researcher Award.