Safaa Najah Saud Al-humairi | Design of Experiments | Editorial Board Member

Published on by Statistics

Editorial Board Member

Safaa Najah Saud Al-humairi,
Management and Science University.

Safaa Najah Saud Al-humairi is a researcher affiliated with Management and Science University, Malaysia. Her stated research subject area is nanotechnology. Her scholarly profile reports 3,108 citations, an h-index of 32, and an i10-index of 73, according to the supplied profile information. [1]

Safaa Najah Saud Al-humairi
Affiliation Management and Science University
Country Malaysia
Citations 3,108
h-index 32
i10-index 73
Subject Area Nanotechnology
Event World Statistics Award

Abstract

This article presents the academic profile of Safaa Najah Saud Al-humairi, affiliated with Management and Science University in Malaysia. The supplied information identifies nanotechnology as her subject area and reports 3,108 citations, an h-index of 32, and an i10-index of 73. These indicators provide a bibliometric overview, subject to verification against the original scholarly profile. [1]

Keywords

Safaa Najah Saud Al-humairi, nanotechnology, research profile, bibliometrics, citation analysis, h-index, i10-index, scholarly publications, academic recognition, Management and Science University, Malaysia, World Statistics Award. [1]

Introduction

Safaa Najah Saud Al-humairi is presented as a researcher affiliated with Management and Science University in Malaysia, with nanotechnology identified as her subject area. Her scholarly profile provides a basis for examining research visibility through citation indicators. This article summarizes the supplied information while distinguishing reported metrics from independently verified academic records. [1]

Research Profile

The supplied profile associates Safaa Najah Saud Al-humairi with Management and Science University and identifies nanotechnology as her research subject. Reported bibliometric indicators include 3,108 citations, an h-index of 32, and an i10-index of 73. These figures describe citation activity but do not independently establish publication quality, research methods, or individual contributions. [1]

Research Contributions

Nanotechnology encompasses research involving materials and systems at very small scales, with applications across multiple scientific and technological fields. The supplied profile identifies this broad subject area but does not specify individual studies, methods, or discoveries attributable to the researcher. Specific contributions should therefore be described using verified publications, abstracts, and documented research findings. [1]

Publications

The researcher’s Google Scholar profile provides a starting point for reviewing indexed scholarly publications, co-authorship, and citation activity. However, a complete publication list, article titles, journal details, publication dates, and DOI identifiers were not included in the supplied information. Individual publications should be checked against their original publisher records before being listed or cited as evidence of research output. [1]

Research Impact

The supplied bibliometric figures report 3,108 citations, an h-index of 32, and an i10-index of 73. Citations can indicate that scholarly work has been referenced by other publications, while the h-index reflects publication and citation performance together. These indicators vary by database and date and should be interpreted alongside research quality, field norms, and documented contributions. [1]

Award Suitability

The World Statistics Award provides the stated recognition context for this academic profile. The researcher’s reported citation indicators may serve as supporting information during an assessment, but they do not alone establish eligibility or award merit. A fair evaluation should consider verified publications, methodological rigor, relevance to the award criteria, documented contributions, and the accuracy of the submitted academic record. [1] [2]

Conclusion

Safaa Najah Saud Al-humairi’s supplied academic profile identifies an affiliation with Management and Science University in Malaysia and a subject area of nanotechnology. Reported citation indicators offer an initial view of scholarly visibility. Further assessment requires verification of publication records, research contributions, institutional details, and alignment with the World Statistics Award’s published recognition criteria. [1] [2]

References

  1. Google Scholar. (n.d.). Scholar profile: Safaa Najah Saud Al-humairi. Profile and bibliometric information supplied for this article. Retrieved October 21, 2026.

    https://scholar.google.com/citations?user=k3ISRbcAAAAJ&hl=en&oi=ao

  2. Saud, S. N., Hamzah, E., Abubakar, T., Bakhsheshi-Rad, H. R., Yusop, M. Z., & Tanemura, M. (2014). Effects of Mn additions on the structure, mechanical properties, and corrosion behavior of Cu-Al-Ni shape memory alloys. Journal of Materials Engineering and Performance.

    https://doi.org/10.1007/s11665-014-1134-1

  3. Wahid, M. A., Hosseini, S. E., Hussen, H. M., Akeiber, H. J., Saud, S. N., & Mohammad, A. T. (2017). An overview of phase change materials for construction architecture thermal management in hot and dry climate region.

    https://doi.org/10.1016/j.applthermaleng.2016.07.032

Esra Cakir | Fuzzy Statistics and Uncertainty Modelling | Innovative Research Award

Published on by Statistics

Innovative Research Award

Esra Cakir,
Affiliation Galatasaray University
Country Turkey
Scopus ID 57210106850
Documents 50
Citations 286
h-index 9
Subject Area Fuzzy set theory
Event World Statistics Awards
ORCID 0000-0003-4134-7679

Esra Cakir,
Galatasaray University

Esra Cakir, affiliated with Galatasaray University, has contributed to research in fuzzy set theory through scholarly publications addressing mathematical modeling, uncertainty analysis, and decision-making methodologies. Her publication record, citation performance, and continuing academic engagement demonstrate sustained contributions to statistics and applied mathematical sciences within an international research environment.[1]

Abstract

Esra Cakir’s academic activities focus on fuzzy set theory and related statistical methodologies that support uncertainty modeling, optimization, and intelligent decision-making. Her research portfolio reflects continued publication in peer-reviewed journals and measurable scholarly influence through citations, contributing to mathematical sciences and interdisciplinary statistical applications.[1] [2]

Keywords

Fuzzy Set Theory, Statistics, Decision Making, Mathematical Modeling, Optimization, Uncertainty Analysis, Applied Mathematics, Data Analysis, Intelligent Systems, Scientific Research.[2]

Introduction

Esra Cakir has established an academic presence through research in fuzzy set theory, emphasizing mathematical approaches for uncertainty and decision analysis. Her work supports statistical modeling and interdisciplinary applications while contributing to peer-reviewed scientific literature that advances quantitative research methodologies across multiple domains.[1] [2]

Research Profile

Affiliated with Galatasaray University, Esra Cakir has authored fifty indexed publications and accumulated 286 citations with an h-index of nine. Her research addresses fuzzy systems, mathematical reasoning, and statistical techniques, demonstrating consistent scholarly productivity and international academic visibility through recognized indexing databases.[1] [3]

Research Contributions

Her contributions include developing and applying fuzzy set methodologies for uncertainty evaluation, decision support, and mathematical analysis. These studies encourage improved analytical frameworks across statistics and related disciplines while promoting interdisciplinary collaboration and methodological refinement within contemporary quantitative research environments.[2] [3]

Publications

Esra Cakir’s publication record comprises fifty Scopus-indexed documents covering fuzzy mathematics, statistical modeling, and decision sciences. These publications demonstrate continuing research activity, collaboration with academic peers, and dissemination of findings through internationally recognized scholarly journals and conference proceedings.[1] [4]

Research Impact

With 286 citations and an h-index of nine, her research demonstrates measurable academic influence. Citation performance indicates that her published studies continue supporting subsequent investigations, reflecting sustained relevance within fuzzy set theory, statistical methodologies, and interdisciplinary mathematical research communities.[1] [3]

Award Suitability

The Innovative Research Award appropriately recognizes sustained scholarly productivity, meaningful publication output, and contributions to fuzzy set theory. Her documented research achievements, citation record, and continuing engagement with advanced statistical methodologies align with the objectives of international academic recognition programs.[1] [2]

Conclusion

Esra Cakir’s academic profile reflects continuous contributions to fuzzy set theory through publications, citations, and collaborative research. Her scholarly achievements demonstrate professional consistency and support her recognition within the World Statistics Awards as a researcher contributing to contemporary statistical and mathematical sciences.[1] [3]

References

  1. Elsevier. (n.d.). Scopus author details: Esra Cakir, Author ID 57210106850. Scopus.

    https://www.scopus.com/pages/authors/57210106850

  2. ORCID. (n.d.). Esra Cakir ORCID Record: 0000-0003-4134-7679.

    https://orcid.org/0000-0003-4134-7679

  3. Çakır, E. (2026). Energy-efficient and sustainable milk-run optimization for e-scooter battery routing under fuzzy time windows. IEEE Transactions on Industry Applications.

    https://doi.org/10.1109/TIA.2026.3680469

  4. World Statistics Awards. (n.d.). Innovative Research Award.

    https://statisticsaward.com

Guo Tian | Machine Learning and Statistics | Best Researcher Award

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Assoc Prof. Dr. Guo Tian | Machine Learning and Statistics | Best Researcher Award

Tsinghua University | China

Assoc Prof. Dr. Guo Tian is an accomplished young chemical engineer whose research lies at the frontier of sustainable catalysis and CO₂/CO conversion. He earned his Bachelor’s degree in Chemical Engineering under Prof. Xuezhi Duan at the East China University of Science and Technology and pursued his doctoral studies in Chemical Engineering at Tsinghua University under the guidance of Prof. Fei Wei. Following his doctoral training, he joined Southwest Jiaotong University as an Associate Professor and Principal Investigator. At only twenty-five years of age, Guo has led pioneering work on high-pressure thermo-catalytic systems, including the design of a reactor capable of stable operation at up to 60 bar integrated with surface-enhanced infrared absorption spectroscopy (SEIRAS) for in-situ monitoring of reaction intermediates. His studies have revealed critical mechanistic pathways in CO/CO₂ conversion using bifunctional catalysts, identifying oxygenate intermediates as key to improving the traditional methanol-to-hydrocarbons (MTH) mechanism. Drawing inspiration from biological systems, he has advanced the concept of bio-inspired multifunctional catalysts and introduced the innovative idea of “catalytic shunt” strategies to enhance selectivity and efficiency. Combining experimental research with density-functional theory (DFT) and micromodel simulations, his work bridges molecular-level understanding with reactor-scale engineering. Dr. Tian has authored numerous influential publications in high-impact journals such as Nature Sustainability, Nature Communications, ACS Catalysis, and the Journal of the American Chemical Society. Notable among these are “Efficient syngas conversion via catalytic shunt” (Nature Sustainability), and “Upgrading CO₂ to sustainable aromatics via perovskite-mediated tandem catalysis” (Nature Communications). According to his Scopus profile, he has authored 14 documents, accumulated around 297 citations, and holds an h-index of 9, reflecting a strong and growing impact in the field. His expertise includes thermochemical measurement and data analysis, catalytic materials design, reactor and reaction-system development, in-situ spectroscopy (SEM, XRD, XPS, XAS), and DFT-based theoretical modeling. Integrating theory, advanced characterization, and engineering innovation, Guo Tian’s vision focuses on transforming CO₂ and CO into high-value sustainable fuels such as aviation fuel components, contributing to global carbon-neutral energy goals. Through his scientific rigor, leadership, and creativity, he has rapidly emerged as a rising star in heterogeneous catalysis and sustainable chemical engineering.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

M. Zhao, Q. Wu, X. Chen, H. Xiong, G. Tian, L. Yan, F. Xiao, & F. Wei. (2025). Entropy-governed zeolite intergrowth. Journal of the American Chemical Society.

Z. Wang, X. Liu, G. Tian, Z. Wang, L. Li, F. Lu, Y. Yu, Z. Li, F. Wei, & C. Zhang. (2025). Research advances in coal-based syngas to aromatics technology. Clean Energy, 9(5), 136–152.

J. He, G. Tian, D. Liao, Z. Li, Y. Cui, F. Wei, C. Zeng, & C. Zhang. (2025). Mechanistic insights into methanol conversion and methanol-mediated tandem catalysis toward hydrocarbons. Journal of Energy Chemistry.

H. Xiong, Y. C. Wang, X. Liang, M. Zhao, G. Tian, G. Wang, L. Gu, & X. Chen. (2025). In situ quantitative imaging of nonuniformly distributed molecules in zeolites. Journal of the American Chemical Society, 147(32), 28965–28972.

Z. Li, J. Chen, G. Xu, Z. Tang, X. Liang, G. Tian, F. Lu, Y. Yu, Y. Wen, & J. Yang. (2025). Constructing three-dimensional covalent organic framework with aea topology and flattened spherical cages. Chemistry of Materials, 37(5), 1942–1948.

Ching Chih Tsai | Fuzzy Statistics and Uncertainty Modelling | Best Researcher Award

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Prof. Ching Chih Tsai | Fuzzy Statistics and Uncertainty Modelling | Best Researcher Award

Prof. Ching Chih Tsai |  National Chung Hsing University | Taiwan

Prof. Ching Chih Tsai is a distinguished academic in electrical engineering and control systems, currently serving as a Life Distinguished Professor at the Department of Electrical Engineering, National Chung Hsing University (NCHU), Taiwan. He earned his Ph.D. from Northwestern University in 1991. Dr. Tsai has held significant leadership roles, including serving as the President of the Chinese Automatic Control Society (CACS), the Robotics Society of Taiwan (RST), and the International Fuzzy Systems Association (IFSA). He has also been a Board of Governors member of IEEE Systems, Man, and Cybernetics Society (SMCS) and is currently the Dean of the College of Electrical Engineering and Computer Science at NCHU. An IEEE Fellow, his research focuses on intelligent control systems, mobile robotics, and automation intelligence. Dr. Tsai has published over 700 technical articles, with more than 20 in the International Journal of Fuzzy Systems since 2005. His recent work includes a 2025 paper on intelligent adaptive formation control for multi-quadrotors, introducing a hybrid controller combining Output Recurrent Fuzzy Broad Learning Systems (ORFBLS), reinforcement learning, and adaptive backstepping sliding mode control. According to Scopus, he has an h-index of 29, with 3,902 citations from 272 documents.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Rospawan, A., Tsai, C.-C., & Hung, C.-C. (2025). Two-layer intelligent learning control using output recurrent fuzzy neural long short-term memory broad learning system with RMSprop. IEEE Access.

Tsai, C.-C., Hung, C.-C., Mao, C.-F., Wu, H.-S., & Chen, C.-H. (2025). Fuzzy neural LSTM-RBLS for fractional-order PID sliding-mode motion control of autonomous mobile robots with four ISID wheels. International Journal of Fuzzy Systems.

Tsai, C.-C., Mao, C.-F., & Hussain, K. (2025). Intelligent adaptive formation control using ORFBLS and reinforcement learning for uncertain tilting multi-quadrotors. International Journal of Fuzzy Systems. =

Rospawan, A., Tsai, C.-C., & Hung, C.-C. (2025). Intelligent MIMO ORFBLS-based setpoint tracking control with its application to temperature control of an industrial extrusion barrel. International Journal of Fuzzy Systems.

Tsai, C.-C., Huang, H.-C., Chen, H.-Y., Hung, C.-C., & Chen, S.-T. (2024). Intelligent collision-free formation control of ball-riding robots using output recurrent broad learning in industrial cyber-physical systems. IEEE Transactions on Industrial Cyber-Physical Systems.