Qingmin Wang | Statistical Computing and Programming | Innovative Research Award

Published on by Statistics

Innovative Research Award

Qingmin Wang,
Zhejiang University.

Qingmin Wang
Affiliation Zhejiang University
Country China
Scopus ID 57322536800
Documents 25
Citations 342
h-index 12
Subject Area Civil Engineering
Event World Statistics Awards
ORCID 0000-0001-6353-7014

Qingmin Wang is a researcher affiliated with Zhejiang University whose indexed scholarly record includes 25 documents, 342 citations, and an h-index of 12. His stated subject area is Civil Engineering. These bibliometric indicators provide a structured overview of his documented research activity and scholarly visibility. [1]

Abstract

Qingmin Wang is affiliated with Zhejiang University, China, and is associated with the field of Civil Engineering. Available bibliometric information records 25 scholarly documents, 342 citations, and an h-index of 12. This article summarizes the documented research profile, contributions, publications, scholarly impact, and relevance to the Innovative Research Award. [1]

Keywords

Civil Engineering; statistical analysis; engineering research; research publications; bibliometrics; scholarly impact; Innovative Research Award; World Statistics Awards.

Introduction

Qingmin Wang is affiliated with Zhejiang University in China and works within Civil Engineering. His documented scholarly profile comprises 25 Scopus-indexed documents, 342 citations, and an h-index of 12. These indicators offer measurable context for reviewing his research activity, publication record, and academic visibility in engineering research. [3]

Research Profile

Wang’s research profile is situated within Civil Engineering and is supported by a documented Scopus author record. The profile identifies Zhejiang University as his affiliation and records 25 documents, 342 citations, and an h-index of 12. These metrics provide quantitative indicators for examining his scholarly output and citation visibility. [1]

Research Contributions

Wang’s documented contributions can be considered through his publication activity and indexed citation record in Civil Engineering. His 25 recorded documents represent a body of scholarly output, while 342 citations indicate subsequent academic referencing. Together, these measures provide evidence for assessing the reach and continuity of his research contributions. [2]

Publications

The available Scopus record identifies 25 documents associated with Qingmin Wang. The indexed publication count provides a measurable basis for describing his scholarly productivity. Individual publication titles, journals, publication years, and DOI information should be verified against authoritative publisher and indexing records before being used for detailed bibliographic analysis. [3]

Research Impact

The recorded citation count of 342 and h-index of 12 provide quantitative measures of Wang’s scholarly visibility within indexed research literature. Citation metrics can help describe how publications have been referenced by subsequent studies, although they should be interpreted alongside publication quality, research context, collaboration, and disciplinary citation practices. [2]

Award Suitability

For the Innovative Research Award, Wang’s documented affiliation, Civil Engineering subject area, publication activity, and citation record provide relevant evidence for consideration. The available metrics indicate an established indexed research profile. Final award assessment should additionally consider submitted research materials, originality, methodological quality, significance, and the evaluation criteria established by the World Statistics Awards. [2]

Conclusion

Qingmin Wang’s academic profile is associated with Zhejiang University and Civil Engineering, with 25 indexed documents, 342 citations, and an h-index of 12. These indicators establish a measurable record of scholarly activity and visibility. Further evaluation can incorporate publication details, research originality, methodological contributions, and supporting academic documentation. [1]

References

  1. Zhao, W., Chang, T., Wang, Q., Li, Y., Cui, Y., Yang, Y., & Sun, B. (2026). Tensile performance of the vertical joint of a novel precast RC shear wall structure with concentrated connection bars: Experimental and numerical investigation. Journal of Building Engineering.

    https://doi.org/10.1016/j.jobe.2026.117242

  2. Zhao, W., Zheng, T., Li, Y., Yang, Y., & Wang, Q. (2025). Shear behavior of keyed vertical joints with lap splices for precast RC frame-shear wall structures. Engineering Structures.

    https://doi.org/10.1016/j.engstruct.2025.121100

  3. Yuan, L., Yang, Y., Wang, Q., Zhao, Q., Cui, Y., & Zhao, W. (2025). Investigation on the dimensions design and anchorage mechanism of headed bars utilized as shear reinforcements.

    https://doi.org/10.1016/j.istruc.2025.108647

Taowei Liu | Machine Learning and Statistics | Best Researcher Award

Published on by Statistics

 

Best Researcher Award

Taowei Liu,
Changsha University of Science and Technology.

Taowei Liu
Affiliation Changsha University of Science and Technology
Country China
Scopus ID 60767546000
Subject Area Drone Technology, 3D Modeling, Dung Beetle Optimization Algorithm, High-Precision Modeling
Event World Statistics Awards

Taowei Liu is a researcher affiliated with Changsha University of Science and Technology, China, whose stated research interests encompass drone technology, three-dimensional modeling, optimization algorithms, and high-precision modeling. These areas represent interdisciplinary applications connecting computational methods, engineering systems, and intelligent modeling approaches. [1]

Abstract

Taowei Liu’s research profile is associated with computational and engineering-oriented topics involving drone technology, 3D modeling, optimization algorithms, and high-precision modeling. The combination of these areas suggests an interdisciplinary research direction involving intelligent computation, geometric representation, optimization, and technology-enabled modeling applications. [1]

Keywords

  • Drone Technology
  • 3D Modeling
  • Dung Beetle Optimization Algorithm
  • High-Precision Modeling
  • Computational Optimization

Introduction

Taowei Liu is affiliated with Changsha University of Science and Technology and works within research areas connecting drone technology, computational modeling, optimization, and engineering applications. His identified subject areas indicate an interdisciplinary approach to developing computational techniques for representing, optimizing, and improving the precision of complex technical models and systems. [1]

Research Profile

Liu’s documented research profile encompasses drone technology, three-dimensional modeling, the Dung Beetle Optimization Algorithm, and high-precision modeling. These subjects combine engineering, computational intelligence, geometric representation, and optimization. The profile therefore reflects research activity positioned at the intersection of intelligent algorithms, digital modeling, and technology-driven engineering problem solving. [2]

Research Contributions

Liu’s identified contributions are centered on computational approaches relevant to drone systems, 3D modeling, optimization, and precision-oriented modeling. In particular, the application of optimization algorithms to technical modeling problems represents a methodological direction capable of supporting improved computational efficiency, model refinement, and accuracy in engineering-oriented research contexts. [1]

Publications

The supplied researcher information identifies Taowei Liu’s research domains but does not provide a verified publication list or individual DOI records. Accordingly, specific publications and DOI identifiers are not assigned here without source verification. The Scopus author profile provides the appropriate source for reviewing indexed documents and publication information associated with Author. [2]

Research Impact

The potential research impact of Liu’s subject areas lies in combining intelligent optimization with digital modeling and drone-related technologies. High-precision modeling can support engineering analysis and digital representation, while optimization methods may assist computational decision processes. Verified citation counts, document totals, and h-index values were not supplied for quantitative assessment. [1]

Award Suitability

Liu’s research themes are potentially relevant to a Best Researcher Award because they encompass interdisciplinary work involving computational optimization, drone technology, 3D modeling, and precision-oriented engineering. Final award suitability should be determined through documented publications, research originality, scholarly impact, citation evidence, and independent evaluation against the World Statistics Awards’ applicable criteria. [2]

Conclusion

Taowei Liu presents a research profile focused on drone technology, 3D modeling, optimization algorithms, and high-precision modeling. These interconnected areas demonstrate a computational and engineering-oriented research direction. Further assessment of scholarly influence should rely on verified publications, citations, indexing information, and documented research outcomes available through authoritative academic sources. [1]

References

  1. Elsevier. (n.d.). Scopus author details: Taowei Liu, Author ID 60767546000. Scopus.

    https://www.scopus.com/pages/authors/60767546000

  2. Liu, T. (2026). 3D modeling of bridge piers based on drone technology and dung beetle optimization algorithm. In D.-S. Huang, B. Li, Q. Zhang, & W. Bao (Eds.), Advanced intelligent computing technology and applications: 22nd International Conference on Intelligent Computing (ICIC 2026).

    https://link.springer.com/chapter/10.1007/978-981-92-3492-9_6

Shanshan Wang | Machine Learning and Statistics | Best Researcher Award

Published on by Statistics

Best Researcher Award

Shanshan Wang,
University of Jinan

Shanshan Wang
Affiliation University of Jinan
Country China
Citations 1,094
h-index 12
i10 Index 13
Subject Area Computer Science and Technology
Event World Statistics Awards
ORCID 0000-0002-8620-9766

Shanshan Wang is a researcher affiliated with the University of Jinan, China, whose academic profile is situated within Computer Science and Technology. Available bibliometric information records 1,094 citations, an h-index of 12, and an i10 index of 13, providing measurable indicators of research visibility and scholarly influence.[1][2]

Abstract

Shanshan Wang, affiliated with the University of Jinan in China, is presented as a candidate for the Best Researcher Award based on documented academic indicators and a research focus in Computer Science and Technology. The profile records 1,094 citations, h-index 12, and i10 index 13, supporting assessment of scholarly activity.[1][2]

Keywords

  • Shanshan Wang
  • University of Jinan
  • Computer Science and Technology
  • Research Excellence
  • Bibliometric Impact
  • Best Researcher Award
  • World Statistics Awards

Introduction

Shanshan Wang is a researcher at the University of Jinan, China, working within Computer Science and Technology. The available academic indicators provide a quantitative basis for reviewing scholarly activity, including 1,094 citations, an h-index of 12, and an i10 index of 13. These measures support a structured assessment of research development.[1][2]

Research Profile

Wang’s research profile is associated with Computer Science and Technology and reflects an academic career focused on research and scholarly dissemination. Bibliometric information indicates sustained citation activity and documented influence within the scholarly record. The profile is additionally connected with ORCID identifier 0000-0002-8620-9766, supporting researcher identity and publication disambiguation.[1][2]

Research Contributions

Wang’s documented contribution is represented through research activity in Computer Science and Technology and its associated scholarly impact. The available citation indicators suggest that published research has received attention from subsequent academic work. An h-index of 12 and i10 index of 13 provide complementary measures for evaluating citation distribution and the presence of repeatedly cited publications.[1]

Publications

Wang’s scholarly publications form an important component of the research profile and provide the primary basis for evaluating academic contributions. The supplied information confirms a Google Scholar profile containing the researcher’s indexed works, while the available bibliometric indicators record 1,094 citations and an i10 index of 13. Individual DOI details should be verified against source records.[1][3]

Research Impact

Research impact can be assessed through citation activity, publication visibility, and sustained scholarly recognition. Wang’s reported total of 1,094 citations and h-index of 12 indicates that the researcher’s work has been referenced across the academic literature. These indicators provide quantitative evidence for considering the reach and influence of contributions within Computer Science and Technology.[1]

Award Suitability

The available profile supports consideration of Shanshan Wang for a Best Researcher Award through a combination of institutional affiliation, subject-area relevance, citation performance, and identifiable scholarly output. The reported h-index of 12, i10 index of 13, and 1,094 citations provide measurable evidence for evaluation, subject to the award’s formal eligibility and verification procedures.[1][2]

Conclusion

Shanshan Wang’s academic profile demonstrates research engagement in Computer Science and Technology, supported by measurable citation indicators and researcher-identification records. The reported 1,094 citations, h-index of 12, and i10 index of 13 establish a quantitative foundation for recognition. Final award assessment should consider verified publications, originality, contribution, and documented research significance.[1][2]

References

  1. ORCID. (n.d.). ORCID record for Shanshan Wang, ORCID 0000-0002-8620-9766.

    https://orcid.org/0000-0002-8620-9766

  2. Google Scholar. (n.d.). Shanshan Wang — Google Scholar profile and publications.

    https://scholar.google.com/citations?hl=zh-CN&user=GMgHNBUAAAAJ&view_op=list_works&sortby=pubdate

  3. World Statistics Awards. (n.d.). World Statistics Awards.

    https://statisticsaward.com/