Norhidayah Mohamad | Engineering | Innovative Research Award | 4631

Published on | Editorial Board by World Top Scientists

 

Innovative Research Award

Norhidayah Mohamad  |  Institution: MMU, Malaysia

Norhidayah Mohamad
Affiliation MMU
Country Malaysia
Google Scholar ID KidB914AAAAJ
Documents 28
Citations 60
h-index 4
Subject Area Engineering
Event World Top Scientist Awards
ORCID 0000-0003-1438-4925

Norhidayah Mohamad is a researcher affiliated with MMU in Malaysia whose academic profile is associated with the field of Engineering. This article presents a structured scholarly overview prepared in relation to the Innovative Research Award at the World Top Scientist Awards. The assessment framework considers the supplied research indicators, publication activity, scholarly contributions, citation visibility, and relevance of the research profile to innovation-oriented academic recognition.[1]

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

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

Zeeshan Haider Jaffari | Engineering | Research Excellence Award

Published on | Editorial Board by World Top Scientists

Research Excellence Award

Zeeshan Haider Jaffari
Researcher Zeeshan Haider Jaffari
Affiliation Morgan State University
Country United States
Scopus ID 57201651125
Documents 33
Citations 1,461
h-index 20
Subject Area Engineering
Event World Top Scientist Awards

Zeeshan Haider Jaffari – Morgan State University

Zeeshan Haider Jaffari, affiliated with Morgan State University, has established a multidisciplinary research profile within engineering through contributions spanning environmental engineering, photocatalysis, machine learning applications, hydrogen energy, wastewater treatment, and sustainable materials. His published scholarly work, citation performance, and collaborative research activities demonstrate sustained academic engagement across internationally recognized journals. The following article summarizes his research profile, scholarly contributions, publication record, research influence, and overall suitability for international scientific recognition.[1]

Abstract

Zeeshan Haider Jaffari has developed an active research portfolio emphasizing engineering solutions for environmental sustainability, advanced materials, renewable energy technologies, and machine learning driven predictive modeling. His scholarly publications demonstrate interdisciplinary collaboration while addressing practical scientific challenges involving wastewater remediation, adsorption processes, photocatalysis, and hydrogen production. The measurable citation impact, publication consistency, and international research visibility indicate meaningful academic influence. This profile reviews his research achievements, publication history, scientific impact, and professional recognition within engineering while considering the relevance of these accomplishments for international academic awards and research excellence.[1]

Keywords

Engineering, Environmental Engineering, Photocatalysis, Hydrogen Energy, Machine Learning, Wastewater Treatment, Sustainable Materials, Adsorption, Artificial Intelligence, Renewable Energy.

Introduction

Engineering research increasingly integrates computational intelligence with sustainable technologies to solve environmental challenges. Within this evolving landscape, Zeeshan Haider Jaffari has contributed to research focusing on wastewater treatment, photocatalytic materials, adsorption science, renewable energy, and predictive analytical methods. His collaborations across international institutions demonstrate engagement with interdisciplinary scientific initiatives that address contemporary environmental and engineering problems through experimental investigation and data-driven methodologies.[2]

Research Profile

The research profile of Zeeshan Haider Jaffari reflects sustained scholarly productivity supported by thirty-three Scopus-indexed publications, more than fourteen hundred citations, and an h-index of twenty. His investigations span environmental remediation, catalytic materials, machine learning prediction systems, sustainable engineering, and energy applications. These indicators collectively demonstrate consistent academic participation and measurable international visibility within engineering research communities.[1]

Research Contributions

His published studies explore photocatalytic degradation, adsorption technologies, hydrogen production, wastewater purification, and artificial intelligence assisted prediction models. Several investigations integrate experimental engineering with computational analysis, improving predictive capability while supporting environmentally sustainable solutions. These multidisciplinary contributions demonstrate practical relevance for resource management, environmental protection, and advanced engineering research conducted through international scientific collaboration.[3]

Publications

The publication record includes research articles published in internationally recognized journals covering environmental engineering, cleaner production, hydrogen energy, adsorption science, and computational engineering. Recent studies investigate machine learning applications for pollutant degradation prediction, phosphate adsorption, photocatalytic fuel cells, and sustainable treatment technologies. The diversity of publication topics reflects interdisciplinary collaboration and continuous engagement with emerging engineering challenges through evidence-based scientific research.[3]

Research Impact

Research impact can be evaluated through publication productivity, citation performance, scholarly visibility, and collaborative influence. With more than 1,461 citations and an h-index of 20, the research demonstrates continued academic recognition within engineering disciplines. The integration of sustainable technologies with artificial intelligence further increases the relevance of these investigations for environmental engineering, renewable energy, and industrial applications across international research communities.[1]

Award Suitability

Based on available scholarly indicators, Zeeshan Haider Jaffari demonstrates characteristics commonly associated with international research recognition, including sustained publication activity, measurable citation performance, interdisciplinary collaboration, and contributions addressing significant engineering and environmental challenges. These achievements indicate a research profile consistent with evaluation criteria frequently considered for global scientific recognition programs such as the World Top Scientist Awards while remaining subject to independent assessment by the award committee.[4]

Conclusion

Zeeshan Haider Jaffari has established a scholarly record characterized by interdisciplinary engineering research, international collaboration, and measurable scientific impact. His publications addressing sustainable engineering, environmental remediation, artificial intelligence, and renewable energy contribute to contemporary scientific knowledge while demonstrating continued academic productivity. Collectively, these accomplishments support recognition as an active researcher whose work has achieved international visibility through publications, citations, and collaborative scientific engagement.[1]

External Links

References

  1. Ishtiaq, R., Rehan, Abbas, A., Lam, S., & Jaffari, Z. H. (2025). Machine learning powered prediction of photodegradation of 2,4-dichlorophenoxyacetic acid using gold-doped bismuth ferrite. Cleaner Water, 4, 100163. https://doi.org/10.1016/j.clwat.2025.100163
  2. Iftikhar, S., Ishtiaq, R., Zahra, N., Abbas, A., & Jaffari, Z. H. (2025). Probabilistic prediction of phosphate ion adsorption onto biochar materials using a large dataset and online deployment. Chemosphere, 370, 144031.https://doi.org/10.1016/j.chemosphere.2024.144031
  3. Elsevier. (n.d.). Scopus author profile: Zeeshan Haider Jaffari (Author ID: 57201651125). Scopus Preview.https://www.scopus.com/authid/detail.uri?authorId=57201651125

 

Dongfeng Qi | Engineering | Best Researcher Award

Published on | Editorial Board by World Top Scientists

Prof. Dongfeng Qi | Engineering | Best Researcher Award

Professor | Shandong University of Technology | China

Prof. Dongfeng Qi is a leading researcher in laser manufacturing and material processing, specializing in femtosecond and nanosecond laser applications for advanced materials and flexible electronics. His work integrates theoretical modeling with experimental techniques to develop innovative micro- and nanostructures, including copper and silicon-based materials, phase-change films, and smart electronic devices. Prof. Qi has made substantial contributions to understanding laser-material interactions and patterning technologies, with high-impact publications in top-tier journals. He demonstrates strong interdisciplinary collaboration and mentorship, fostering international research partnerships and the growth of emerging scientists. His research is recognized for both fundamental insights and practical applications in photonics, energy storage, and flexible electronics. Prof. Qi’s consistent innovation, high-quality experimental work, and leadership in the field establish him as a leading figure in laser-based materials science. According to Scopus, he has 535 citations, 71 documents, and an h-index of 13.

Profiles: Scopus | Google Scholar

Featured Publications

1. Programming nanoparticles in multiscale: optically modulated assembly and phase switching of silicon nanoparticle array; L. Wang, Y. Rho, W. Shou, S. Hong, K. Kato, M. Eliceiri, M. Shi, …; ACS Nano, vol. 12, no. 3, pp. 2231–2241, 2018; 39 citations

2. Time-resolved analysis of thickness-dependent dewetting and ablation of silver films upon nanosecond laser irradiation; D. Qi, D. Paeng, J. Yeo, E. Kim, L. Wang, S. Chen, C. P. Grigoropoulos; Applied Physics Letters, vol. 108, no. 21, 2016; 37 citations

3. Femtosecond laser-induced large area of periodic structures on chalcogenide glass via twice laser direct-writing scanning process; X. Yu, Q. Zhang, D. Qi, S. Tang, S. Dai, P. Zhang, Y. Xu, X. Shen; Optics & Laser Technology, vol. 124, 105977, 2020; 34 citations

4. Progress in the design, nanofabrication, and performance of metalenses; Z. Wang, Y. Wu, D. Qi, W. Yu, H. Zheng; Journal of Optics, vol. 24, no. 3, 033001, 2022; 31 citations

5. Progress in preparation and applications of Te-As-Se chalcogenide glasses and fibers; Z. Wu, Y. Xu, D. Qi, Q. Nie, X. Zhang; Infrared Physics & Technology, vol. 102, 102981, 2019; 31 citations