Innovative Research Award

Abstract

This academic recognition article provides a neutral overview of Norhidayah Mohamad’s supplied research profile in the context of the Innovative Research Award. The assessment is situated within Engineering and considers scholarly output, citation-based indicators, research dissemination, professional identification, and the broader importance of innovation within engineering scholarship. Rather than treating individual bibliometric values as independent evidence of research quality, the article adopts a contextual approach in which publication activity and measurable scholarly attention are considered together with the nature and relevance of research contributions.^[3]

Keywords

Innovative Research; Research Impact; Scholarly Publications; Academic Recognition; Citation Analysis; Bibliometrics; Research Profile; ORCID; Research Innovation; MMU; Malaysia; World Top Scientist Awards.

Introduction

Innovation-oriented engineering research contributes to academic and technological development by examining established problems, evaluating alternative approaches, and communicating findings that can inform subsequent research or practical applications. Within this setting, academic recognition is appropriately based on several forms of evidence rather than on a single quantitative indicator. Publication records document scholarly participation, citation data can indicate subsequent academic attention, and persistent identifiers such as ORCID help distinguish researchers and connect research outputs across scholarly information systems.^[2]

Research Profile

Norhidayah Mohamad’s supplied research profile reports 28 scholarly documents, 60 citations, and an h-index of 4, with Engineering identified as the principal subject area. Collectively, these figures describe the scale and recorded visibility of the research portfolio at the time the information was supplied. The h-index combines publication and citation information into a single bibliometric measure; however, responsible interpretation requires awareness that citation accumulation varies according to discipline, database coverage, publication age, document type, and patterns of collaboration.^[3]

Research Contributions

Norhidayah Mohamad’s research focuses on engineering applications in manufacturing, process modelling, and optimization. Her published work demonstrates the application of computational methods and machine learning to solve industrial engineering problems. These studies contribute to improving manufacturing efficiency and engineering performance through analytical approaches.^[2]

Publications

The available publication record shows active research in manufacturing engineering, machine learning, optimization, and advanced materials. Most recent publications appeared in internationally recognized peer-reviewed journals, reflecting continuous scholarly activity and collaboration with researchers from multiple institutions.^[2]

Research Impact

According to the supplied academic profile, Norhidayah Mohamad has published 28 scholarly documents, received approximately 60 citations, and has an h-index of 4. These indicators demonstrate sustained research productivity and continued contribution to engineering scholarship through peer-reviewed publications and collaborative research activities.^[1]

Award Suitability

Norhidayah Mohamad’s research profile demonstrates continuous involvement in engineering and manufacturing research through journal publications and collaborative academic work. Her studies include machine learning, manufacturing optimization, thin-film technology, and sustainable engineering applications. These contributions indicate active participation in multidisciplinary engineering research. ^[2]

Conclusion

Norhidayah Mohamad has established an academic profile centred on engineering research, manufacturing systems, modelling, and industrial applications. Her publications and collaborative research demonstrate continuous scholarly engagement while supporting engineering innovation through analytical and computational approaches. The profile reflects a combination of academic experience, research productivity, and practical engineering knowledge. ^[1]

External Links

• ORCID Profile
  
• Google Scholar Profile
  
• World Top Scientist Awards
  

References

1. Aziz, N. A. A., Aziz, N. H. A., Ghazali, A. K., Mohamad, N., Tobing, S., Auzani, A. S., Hutagaol, D., & Siantar, G. A. L. (2025). Prediction of lift and drag for hydro turbine design using machine learning. Algorithms.
   
   https://doi.org/10.3390/a19010008
   
2. Arifin, N. M., Noor, E. E. M., Mohamad, F., Mohamad, N., & Muzni, N. H. M. (2024). Enhancing the properties of nanostructure TiO₂ thin film via calcination temperature for solar cell application. Energies.
   
   https://doi.org/10.3390/en17143415
   
3. Mohamad, N., Aziz, N. A. A., Ghazali, A. K., & Salleh, M. R. (2024). Improving ammonia emission model of urea fertilizer fluidized bed granulation system using particle swarm optimization for sustainable fertilizer manufacturing practice. Processes.
   
   https://doi.org/10.3390/pr12051025
   
4. Arifin, N. M., Noor, E. E. M., Mohamad, F., & Mohamad, N. (2024). The impact of spinning speed on n-TiO₂/ZnO bilayer thin film fabricated through sol–gel spin-coating method. Coatings.
   
   https://doi.org/10.3390/coatings14010073