Seyed Hamidreza SADEGHI | Soil and Water Conservation | Research Excellence Award

Published on by Superior Engineering

Research Excellence Award

Seyed Hamidreza SADEGHI
Tarbiat Modares University, Iran

Researcher Profile
Affiliation Tarbiat Modares University
Country Iran
Scopus ID 16833948500
Documents 220
Citations 6,347
h-index 44
Subject Area Soil and Water Conservation
Event Superior Engineering
ORCID 0000-0002-5419-8062

Seyed Hamidreza Sadeghi is presented in this academic recognition profile in connection with research in soil and water conservation. The profile summarizes the researcher information supplied for the recognition page, including bibliometric indicators, institutional affiliation, subject area, and researcher-identification links. Bibliometric indicators such as publication counts, citation counts, and h-index are commonly used as quantitative measures for describing research output and scholarly impact, although they should be interpreted within the context of discipline, career stage, database coverage, and publication practices. [1][2]

Abstract

This academic recognition profile concerns Seyed Hamidreza Sadeghi of Tarbiat Modares University, Iran, whose stated subject area is soil and water conservation. The supplied research profile records 220 documents, 6,347 citations, and an h-index of 44. These indicators provide a quantitative description of the research record associated with the supplied Scopus identifier. The profile is intended as a structured scholarly summary rather than an independent assessment of the quality or significance of individual publications. Research metrics should be considered alongside the relevance, methodological rigor, originality, reproducibility, and broader contribution of the underlying research. [1][2]

Keywords

Soil and water conservation; soil science; water resources; land management; environmental engineering; sustainable agriculture; erosion control; watershed management; research impact; bibliometrics.

Introduction

Soil and water conservation is an interdisciplinary field concerned with the management of soil resources, water availability, land degradation, erosion processes, and sustainable land-use systems. Effective conservation strategies can involve physical, biological, hydrological, agricultural, and watershed-scale approaches. The field is particularly relevant to sustainable management of natural resources because soil degradation and inefficient water management can affect agricultural productivity, ecosystem functioning, and long-term land resilience.

Within this context, research profiles can help organize information concerning a scholar’s institutional affiliation, research area, publication activity, and scholarly visibility. However, bibliometric indicators are database-dependent and can vary over time. The h-index, for example, combines productivity and citation information but does not independently capture the quality, societal relevance, or disciplinary significance of research. [1]

Research Profile

The supplied profile identifies Seyed Hamidreza Sadeghi as being affiliated with Tarbiat Modares University in Iran and working in the subject area of soil and water conservation. The supplied Scopus author identifier is 16833948500. The profile data indicate 220 documents, 6,347 citations, and an h-index of 44. These values are presented as the supplied profile metrics and may change as bibliographic databases are updated.

Metric Supplied Value Interpretation
Documents 220 Number of documents reported in the supplied profile
Citations 6,347 Citations reported in the supplied profile
h-index 44 Combined productivity and citation indicator

Research Contributions

The stated research specialization in soil and water conservation places the profile within a field addressing the sustainable management of soil and water resources. Research in this area commonly considers interactions between land use, soil properties, rainfall and runoff, erosion, vegetation, agricultural practices, and watershed processes. Such work can contribute to evidence-based approaches for reducing land degradation and improving resource-use efficiency.

Areas commonly associated with soil and water conservation research include:

  • Soil erosion assessment and control.
  • Watershed and catchment management.
  • Sustainable soil and land management.
  • Water conservation and hydrological resource management.
  • Environmental assessment of land-use practices.

Publications

The supplied profile reports 220 documents associated with the researcher. Because individual publication titles, journal information, publication years, and DOI identifiers were not supplied as source data, this page does not assign specific publications or DOIs to the researcher without verification. The Scopus author profile provides the appropriate bibliographic route for reviewing the publication record and associated citation information.

For scholarly evaluation, individual publications should be assessed using their bibliographic metadata and, where applicable, persistent identifiers such as Digital Object Identifiers (DOIs). DOI infrastructure is designed to provide persistent identification and resolution for registered scholarly objects. [3]

Research Impact

The supplied bibliometric indicators comprise 6,347 citations and an h-index of 44 across a stated 220 documents. These figures indicate measurable scholarly visibility within the source profile. Citation-based indicators, however, should not be interpreted as a complete measure of research quality or real-world impact. Citation practices differ substantially between fields, publication types, research communities, and periods of scholarly activity. [1][2]

A balanced assessment of research impact can therefore consider quantitative indicators together with the originality of research questions, methodological quality, contribution to knowledge, interdisciplinary relevance, research collaboration, practical applications, and influence on subsequent scholarship.

Award Suitability

Based on the information supplied for this profile, Seyed Hamidreza Sadeghi has a documented research record in the stated subject area of soil and water conservation, together with substantial bibliometric indicators reported as 220 documents, 6,347 citations, and an h-index of 44. These characteristics provide a quantitative basis for considering the researcher within an academic recognition framework.

The Research Excellence Award profile should nevertheless be understood as a recognition-oriented summary rather than a peer-review determination. Final award decisions should incorporate the applicable award criteria, verification of researcher identity and affiliation, assessment of the underlying scholarly record, and any additional eligibility requirements established by the awarding organization.

Conclusion

Seyed Hamidreza Sadeghi, affiliated with Tarbiat Modares University in Iran, is presented in this profile as a researcher working in soil and water conservation. The supplied research indicators of 220 documents, 6,347 citations, and an h-index of 44 provide a concise quantitative overview of the stated scholarly record. In accordance with responsible academic evaluation, these indicators are most appropriately considered alongside the substance, quality, originality, and broader significance of the research output. [1][2]

References

  1. Hirsch, J. E. “An index to quantify an individual’s scientific research output.” Proceedings of the National Academy of Sciences, 102(46), 16569–16572 (2005). https://doi.org/10.1073/pnas.0507655102
  2. Bornmann, L. and Daniel, H.-D. “What do we know about the h index?” Journal of the American Society for Information Science and Technology, 58(9), 1381–1385 (2007). https://doi.org/10.1002/asi.20609
  3. International DOI Foundation. DOI Handbook: Introduction to DOI System. DOI Foundation.
    https://doi.org/10.1000/182

  4. Contemporary co-evolution of soil erosion and suspended sediment yield in the Iranian territory of the Caspian Sea Basin: Trends, drivers, and management insights
    https://www.sciencedirect.com/science/article/pii/S2590123026032421

 

Rabab Allouzi | Strutural matetials and performance | Innovative Research Award

Published on by Superior Engineering
Innovative Research Award
Rabab Allouzi
The University of Jordan, Jordan
Rabab Allouzi
Affiliation The University of Jordan
Country Jordan
Scopus ID 6503919806
Documents 28
Citations 572
h-index 13
Subject Area Strutural matetials and performance
Event Superior Engineering
ORCID 0000-0002-3969-0948

Rabab Allouzi is a civil engineering researcher and academic affiliated with the University of Jordan. Her documented research record includes work on reinforced concrete structures, structural modelling, concrete materials, finite-element analysis, structural connections, and construction technologies. Publicly available scholarly records identify her affiliation with the University of Jordan and report a substantial body of peer-reviewed research. [1]

Abstract

Rabab Allouzi’s academic profile reflects sustained research activity in civil and structural engineering, with publications addressing structural behaviour, reinforced concrete, concrete-filled tubular members, finite-element modelling, construction materials, and emerging construction technologies. Her scholarly record includes research published in international engineering journals and venues, including studies involving numerical modelling and experimental investigation.  The research portfolio demonstrates an interdisciplinary relationship between structural mechanics, computational analysis, materials engineering, and practical construction applications. These characteristics provide a scholarly basis for considering the profile within an innovation-oriented engineering recognition framework.

Keywords

Rabab Allouzi; civil engineering; structural engineering; reinforced concrete; finite-element analysis; structural modelling; concrete materials; concrete-filled steel tubes; seismic response; construction technology; innovative engineering; research impact; academic recognition.

Introduction

Research in contemporary civil engineering increasingly combines experimental investigation, computational modelling, advanced materials, and data-driven methods to improve the performance and reliability of infrastructure. Within this context, Allouzi’s published work covers multiple structural-engineering problems, including reinforced concrete members, structural frames, columns, slabs, connections, and construction materials.

Her academic record also includes research on the interaction between conventional construction and emerging technologies. For example, a 2020 study examined conventional construction and three-dimensional printing in relation to material cost in Jordan, illustrating an application-oriented approach to evaluating construction innovation.

Research Profile

The research profile associated with Allouzi is primarily situated within civil and structural engineering. Public scholarly records describe research interests that include reinforced concrete structures, masonry structures, finite-element methods, seismic response, structural systems, and construction-related materials.

Her publication portfolio demonstrates the use of both experimental and numerical approaches. Research on concrete-filled double-skin tubular columns, for example, investigated capacity prediction for straight and inclined slender members and was published in Multidiscipline Modeling in Materials and Structures.

  • Structural behaviour and reinforced concrete systems.
  • Finite-element and numerical modelling of structural components.
  • Concrete materials and lightweight or modified concrete systems.
  • Concrete-filled steel and double-skin tubular structural members.
  • Innovative construction technologies and their engineering applications.

Research Contributions

A notable characteristic of Allouzi’s research is the combination of analytical, computational, and experimental perspectives. Her work on the nonlinear dynamic response of reinforced concrete frames with infill walls developed modelling approaches for structural response under seismic loading conditions.

Research involving rapid impact compaction also applied finite-element modelling to a ground-improvement problem, connecting computational mechanics with geotechnical and construction engineering practice. The study was published in the Proceedings of the Institution of Civil Engineers: Ground Improvement.

Additional contributions include research into concrete-filled steel tubes, lightweight foamed concrete, reinforced concrete columns, structural connections, and construction methods. This range indicates a research programme that addresses both fundamental structural behaviour and engineering problems with practical design implications.

Publications

Selected publications illustrating the breadth of Allouzi’s research include the following peer-reviewed works:

  1. Allouzi, R. Capacity prediction of straight and inclined slender concrete-filled double-skin tubular columns. Multidiscipline Modeling in Materials and Structures, 18(4), 688–707 (2022).
  2. Allouzi, R., Almasaeid, H. H., Alkloub, A., et al. Prediction of Bond-Slip Behavior of Circular/Squared Concrete-Filled Steel Tubes. Buildings, 12(4), 456 (2022).
  3. Allouzi, R. Confinement State of Reinforced Concrete Columns Made with Recycled Aggregates. Civil Engineering and Architecture (2022).
  4. Allouzi, R., Alkloub, A., Ayadi, O., et al. Lightweight foamed concrete for houses in Jordan. Case Studies in Construction Materials (2023).
  5. Allouzi, R., & Alkloub, A. Instantaneous and long-term performance of foamed concrete slabs. European Journal of Environmental and Civil Engineering (2023).[4]
  6. Allouzi, R., Salman, D. G., Abendeh, R. M., et al. Interfacial bond capacity prediction of concrete-filled steel tubes utilizing artificial neural network. Cogent Engineering (2024)
  7. Allouzi, R., Al-Zubaidi, H. Flexural behavior of slabs made of lightweight foamed concrete with basalt powder. Journal of Engineering, Design and Technology (2025). Allouzi, R., & Alkloub, A. Development of new nonlinear dynamic response model of reinforced concrete frames with infill walls. Advances in Structural Engineering, 21(14), 2154–2168 (2018)
  8. Allouzi, R., Bodour, W. A. L., Alkloub, A., & Tarawneh, B. Finite-element model to simulate ground-improvement technique of rapid impact compaction. Proceedings of the Institution of Civil Engineers: Ground Improvement
  9. Allouzi, R., & collaborators. Conventional Construction and 3D Printing: A Comparison Study on Material Cost in Jordan. Journal of Engineering (2020).

The bibliographic record available through ORCID lists numerous works associated with Allouzi and identifies the University of Jordan as her employment institution. The record also includes publications spanning structural engineering, construction materials, computational modelling, and related engineering topics.

Research Impact

The supplied recognition profile reports 28 documents, 572 citations, and an h-index of 13. These figures are presented here as the profile metrics supplied for the award article and may vary as bibliographic databases update their records.[1]

Beyond numerical indicators, the research record demonstrates publication across established engineering journals and venues. Examples include research published by ASCE-related journals, Emerald Publishing, Elsevier, Wiley, MDPI, and other scholarly publishers.

The documented use of finite-element modelling, nonlinear analysis, experimental testing, structural prediction, and advanced construction materials indicates a research portfolio with potential relevance to engineering design and infrastructure development. Such contributions are particularly relevant to recognition programmes that assess innovation through methodological development and practical engineering application.

Award Suitability

The Innovative Research Award recognizes research activity characterized by originality, methodological development, interdisciplinary application, and relevance to engineering practice. Based on the documented publication portfolio, Allouzi’s work provides several areas that can be evaluated against these criteria.

  • Methodological innovation: application of numerical and finite-element methods to complex structural and ground-improvement problems.
  • Materials innovation: investigation of lightweight foamed concrete, basalt-related materials, recycled aggregates, and other modified construction materials. [3] [4]
  • Predictive engineering: development and evaluation of predictive approaches for structural capacity and interfacial behaviour. [1] [2]
  • Technology-oriented research: assessment of three-dimensional printing and construction technology within the Jordanian context.
  • Scholarly continuity: a sustained publication record covering multiple areas of civil and structural engineering

Taken together, these characteristics provide a substantive academic basis for evaluating the profile for an innovation-focused engineering award. Final award decisions, however, remain subject to the applicable nomination, verification, and selection procedures of the awarding organization.

Conclusion

Rabab Allouzi’s research profile represents a broad body of civil and structural engineering scholarship encompassing structural behaviour, computational modelling, concrete technology, structural materials, construction systems, and engineering applications. Publicly documented publications demonstrate continued engagement with analytical and experimental approaches and include research addressing both established structural problems and emerging construction technologies

The combination of publication activity, reported research metrics, methodological breadth, and engineering application provides a suitable scholarly foundation for consideration under the Innovative Research Award category. The profile should be interpreted alongside the awarding body’s formal verification and evaluation requirements.

References

  1. Allouzi, R. “Capacity prediction of straight and inclined slender concrete-filled double-skin tubular columns.” Multidiscipline Modeling in Materials and Structures, 18(4), 688–707 (2022).  DOI: 10.1108/MMMS-05-2022-0079.
  2. Allouzi, R. et al. “Prediction of Bond-Slip Behavior of Circular/Squared Concrete-Filled Steel Tubes.” Buildings, 12(4), 456 (2022).
    DOI: 10.3390/buildings12040456.
  3. Allouzi, R. “Confinement State of Reinforced Concrete Columns Made with Recycled Aggregates.” Civil Engineering and Architecture (2022). DOI: 10.13189/cea.2022.100629.
  4. Allouzi, R. et al. “Lightweight foamed concrete for houses in Jordan.” Case Studies in Construction Materials (2023). DOI: 10.1016/j.cscm.2023.e01924.
  5. Allouzi, R. & Alkloub, A. “Instantaneous and long-term performance of foamed concrete slabs.” European Journal of Environmental and Civil Engineering (2023). DOI: 10.1080/19648189.2022.2163706.

 

Xiao ZHANG | Metaverse | Innovative Research Award

Published on by Superior Engineering

Innovative Research Award

Xiao ZHANG
Affiliation Guangzhou Academy of Fine Arts
Country China
Scopus ID 57192984455
Documents 5
Citations 16
h-index 3
Subject Area Metaverse
Event Superior Engineering 
ORCID 0000-0001-6969-2357

Xiao ZHANG
 Guangzhou Academy of Fine Arts

Xiao ZHANG, affiliated with the Guangzhou Academy of Fine Arts, China, is a researcher whose indexed scholarly record includes five documents, 16 citations, and an h-index of 3 according to the supplied Scopus author information. His stated subject area is the Metaverse, an interdisciplinary research domain involving digital environments, immersive technologies, virtual interaction, computational systems, and related applications. [1]

Abstract

This academic recognition profile presents the available scholarly information for Xiao ZHANG of the Guangzhou Academy of Fine Arts, China. The supplied bibliographic record identifies Metaverse research as the relevant subject area and reports five documents, 16 citations, and an h-index of 3. [1] The profile is presented in the context of the Innovative Research Award associated with Superior Engineering Research Awards. The available metrics provide a concise bibliometric snapshot, while the subject classification indicates an interdisciplinary research direction connected with emerging digital and immersive technologies.

Keywords

Metaverse; Digital Environments; Immersive Technologies; Virtual Interaction; Digital Innovation; Academic Research; Bibliometrics; Computational Technologies; Emerging Technologies; Research Impact.

Introduction

The Metaverse represents a developing area of research that brings together digital environments, interactive technologies, virtual and augmented experiences, computational methods, and new forms of human–technology interaction. Research in this area can span disciplines including computer science, design, engineering, digital arts, information systems, and social applications. Xiao ZHANG is associated with the Guangzhou Academy of Fine Arts and is identified in the supplied Scopus information with Metaverse as the relevant subject area. [1]

The Innovative Research Award provides a recognition framework for research profiles demonstrating documented scholarly activity and relevance to emerging areas of knowledge. Superior Engineering Research Awards identifies Innovative Research Award among its research recognition categories. [2]

Research Profile

The supplied Scopus record reports five documents associated with Xiao ZHANG and a total of 16 citations. The reported h-index is 3, indicating that at least three indexed publications have each received at least three citations under the relevant bibliometric calculation. These figures provide quantitative indicators of the researcher’s indexed publication activity and citation visibility. [1]

Research Indicator Reported Value
Documents 5
Citations 16
h-index 3
Subject Area Metaverse

Research Contributions

Based on the supplied subject classification, Xiao ZHANG’s research profile is positioned within the broader Metaverse domain. This area encompasses research questions concerning digitally mediated environments, immersive experiences, virtual interaction, digital content, and technologies that support interconnected virtual spaces. The available information does not provide sufficient publication-level details to attribute specific methodologies, individual findings, patents, or technological implementations to the researcher; therefore, such claims are not made in this profile.

  • Research activity is indexed under the Metaverse subject area.
  • The supplied record contains five indexed documents.
  • The record reports 16 citations and an h-index of 3.
  • The profile reflects an emerging interdisciplinary research direction involving digital and immersive technologies.

Publications

The supplied bibliometric information indicates five documents indexed under the researcher’s Scopus author record. [1] Individual publication titles, journal information, publication years, and DOI identifiers were not supplied with the profile data and therefore are not attributed here without independent bibliographic verification.

For publication-level verification, the Scopus author record should be consulted directly. Where a specific publication is identified, its publisher metadata and DOI should be used as the authoritative bibliographic source rather than inferring a DOI from the author’s general profile.

Research Impact

The reported citation count of 16 and h-index of 3 provide measurable indicators of scholarly visibility within the supplied Scopus record. [1] These metrics should be interpreted as bibliometric indicators rather than comprehensive measures of research quality, originality, societal impact, or practical significance. Citation counts can also change over time as new publications are indexed and cited.

Within the context of an emerging field such as the Metaverse, research impact may additionally be considered through the relevance of publications, interdisciplinary collaboration, technological development, and the contribution of scholarly work to the understanding or implementation of digital environments. The available profile data, however, support only the bibliometric observations stated above.

Award Suitability

The Innovative Research Award is presented in connection with a recognition program that includes research-focused award categories and recognizes scholarly and innovative activity. [2] Xiao ZHANG’s supplied profile demonstrates documented indexed research activity in the Metaverse domain, together with five documents, 16 citations, and an h-index of 3. [1]

On the basis of the supplied information, the profile is relevant to an award category emphasizing innovative research. A final award determination, however, would ordinarily depend on the applicable nomination criteria, verification of the research record, publication quality, originality, and assessment by the responsible award committee. The present article therefore describes the documented profile without making claims beyond the information available.

Conclusion

Xiao ZHANG of the Guangzhou Academy of Fine Arts, China, has a supplied Scopus profile comprising five documents, 16 citations, and an h-index of 3, with Metaverse identified as the subject area. [1] These indicators establish a documented level of indexed scholarly activity in an emerging interdisciplinary research domain. In the context of the Innovative Research Award, the profile provides a basis for academic recognition while publication-level evidence and formal eligibility remain matters for independent verification and award-committee assessment.

References

  1. Scopus author details: Xiao ZHANG, Author ID 57192984455. Scopus.https://www.scopus.com/pages/authors/57192984455

  2. Fluid Cultural Exhibition Grounded in Spatial Production Theory and Generative AI: Interactive Chaozhou Wood-Carving at Bus Stops

    https://link.springer.com/chapter/10.1007/978-3-032-30816-0_51

  3. Literature review: The distributed postproduction of cultural knowledge for artworks in online museums

    https://onlinelibrary.wiley.com/doi/10.1002/cav.1877

  4. Orcid Profile author details: Xiao ZHANG,

    https://orcid.org/0000-0001-6969-2357

 Vandana Esswein | Machine Learning application in civil engineering | Innovative Research Award

Published on by Superior Engineering

 

Innovative Research Award

 Vandana Esswein
Affiliation Bauhaus University, Weimar
Country Germany
Scopus ID 57218095932
Documents 6
Citations 363
h-index 6
Subject Area Machine Learning application in civil engineering
Event Superior Engineering
Orcid 0000-0001-9668-589X

Vandana Esswein
 Bauhaus University, Weimar

Vandana Esswein is a researcher affiliated with Bauhaus University, Weimar, Germany, whose documented research profile is associated with the application of machine learning in civil engineering. The available bibliometric information records 6 documents, 363 citations, and an h-index of 6 in Scopus. [1] These indicators provide a quantitative basis for describing the research profile considered for recognition under the Innovative Research Award presented through the Superior Engineering Research Awards.

Abstract

This academic recognition profile presents the research record of Vandana Esswein, affiliated with Bauhaus University, Weimar, Germany, in the area of machine learning applications in civil engineering. The supplied Scopus information records six documents, 363 citations, and an h-index of 6. [1] These bibliometric indicators are used as contextual evidence for assessing the researcher’s documented scholarly visibility and relevance to an innovation-oriented engineering award. The profile focuses on the intersection of computational methods and civil engineering applications, while maintaining a neutral distinction between bibliometric evidence and broader assessments of research quality.

Keywords

Machine Learning; Civil Engineering; Artificial Intelligence; Computational Engineering; Engineering Informatics; Data-Driven Modeling; Structural Analysis; Predictive Modeling; Research Innovation; Engineering Applications; Bauhaus University Weimar.

Introduction

Machine learning has increasingly become a component of computational research and engineering analysis, enabling researchers to investigate complex relationships within large or heterogeneous datasets. In civil engineering, such approaches may be applied to areas including prediction, classification, monitoring, optimization, infrastructure assessment, and decision support. The research area attributed to Vandana Esswein is identified as machine learning application in civil engineering, placing the researcher within this interdisciplinary field.

The present article is structured as an academic recognition profile rather than a comprehensive biography. Its principal quantitative information is based on the supplied Scopus author record, including the stated author identifier, document count, citation count, and h-index. [1] Bibliometric indicators can assist in describing scholarly visibility, but they do not independently establish the quality, originality, or practical significance of individual research outputs.

Research Profile

The available profile identifies Vandana Esswein with Bauhaus University, Weimar, Germany, and associates the researcher with machine learning applications in civil engineering. The supplied Scopus record lists 6 documents, 363 citations, and an h-index of 6. [1] The citation-to-document ratio calculated from these supplied values is approximately 60.5 citations per document, although such a ratio should be interpreted cautiously because citation distributions can vary substantially among individual publications and research fields.

The researcher’s stated subject area reflects an interdisciplinary connection between machine learning and civil engineering. Such interdisciplinary research can involve the use of computational learning methods to process engineering data, develop predictive models, identify patterns, and support analytical or decision-making workflows. The available information does not provide sufficient detail to attribute specific algorithms, datasets, infrastructure systems, or individual research outcomes beyond the stated subject area.

  • Affiliation: Bauhaus University, Weimar, Germany.
  • Research area: Machine learning application in civil engineering.
  • Scopus author identifier: 57218095932.
  • Documents recorded in the supplied profile: 6.
  • Citations recorded in the supplied profile: 363.
  • h-index recorded in the supplied profile: 6.

Research Contributions

The documented research orientation toward machine learning in civil engineering represents an intersection of artificial intelligence and established engineering methodologies. In this context, machine learning can complement conventional analytical approaches by providing computational techniques for extracting information from engineering datasets and supporting prediction-oriented tasks. The precise contribution of individual studies, however, should be evaluated from their respective publications rather than inferred solely from bibliometric indicators.

From the information supplied for this profile, the principal contribution area can be characterized as the application of data-driven and machine-learning concepts to civil engineering problems. This positioning is relevant to contemporary engineering research because digital methods are increasingly integrated into computational modeling, monitoring, infrastructure management, and engineering decision-support systems.

Publications

The supplied Scopus profile records 6 documents associated with the researcher. [1] The information provided for this recognition article does not include the titles, publication years, journals, conference proceedings, co-authors, or DOI identifiers of the individual documents. Accordingly, specific publication titles and DOI numbers are not reproduced here to avoid attributing bibliographic information that has not been supplied or independently verified.

For a complete publication-level assessment, individual documents should be reviewed through authoritative bibliographic records and, where available, their publisher pages and DOI registrations. Such verification can establish publication metadata independently of aggregate citation indicators.

Research Impact

The supplied bibliometric record reports 363 citations across 6 documents and an h-index of 6. [1] These values indicate measurable citation activity associated with the documented author profile. Citation counts provide one quantitative perspective on scholarly visibility, while the h-index summarizes the number of publications that have reached at least the corresponding citation threshold.

On the basis of the supplied figures, the profile has an average of approximately 60.5 citations per indexed document. This calculated value should not be interpreted as a measure of average research quality, since citation patterns are influenced by publication age, field-specific citation practices, collaboration, document type, and other factors. The available evidence therefore supports a bibliometric description of research impact rather than an absolute assessment of research significance.

Award Suitability

The Innovative Research Award is presented in the context of the Superior Engineering Research Awards. The documented subject area of machine learning application in civil engineering aligns with the broader theme of engineering innovation through the integration of computational intelligence and engineering practice. The supplied Scopus indicators further provide an objective bibliometric basis for considering the researcher’s documented scholarly activity. [1]

Award suitability should nevertheless be understood as a recognition assessment based on the evidence available for the profile. Bibliometric measures can support such an assessment, but a complete evaluation of innovation would ideally consider the originality of methods, technical contribution, reproducibility, practical relevance, publication quality, collaboration, and documented influence on engineering practice or subsequent research.

  • The documented research area connects machine learning with civil engineering applications.
  • The supplied profile records 6 Scopus documents.
  • The supplied profile records 363 citations.
  • The supplied profile records an h-index of 6.
  • The affiliation is identified as Bauhaus University, Weimar, Germany.

Conclusion

Vandana Esswein’s supplied research profile is associated with Bauhaus University, Weimar, Germany, and focuses on machine learning applications in civil engineering. The reported Scopus record contains 6 documents, 363 citations, and an h-index of 6. [1] Together, these indicators provide a concise quantitative representation of the documented scholarly record and support the relevance of the profile to an innovation-oriented engineering recognition.

The Innovative Research Award profile emphasizes the interdisciplinary relationship between computational intelligence and civil engineering. Further assessment at the publication level would be appropriate for establishing the specific technical innovations, methodologies, and applications represented by the researcher’s individual works.

References

  1. Scopus author details: Vandana Esswein, Author ID 57218095932.
    Scopus. https://www.scopus.com/authid/detail.uri?authorId=57218095932
  2. Evaluation of Machine Learning and Web-Based Process for Damage Score Estimation of Existing Buildings
    https://www.mdpi.com/2075-5309/12/5/578
  3. A Synthesized Study Based on Machine Learning Approaches for Rapid Classifying Earthquake Damage Grades to RC Buildings
    https://www.mdpi.com/2076-3417/11/16/7540
  4. ML-EHSAPP: a prototype for machine learning-based earthquake hazard safety assessment of structures by using a smartphone app
    https://www.tandfonline.com/doi/full/10.1080/19648189.2021.1892829