Mohammadali Arjomand| Academic Excellence Citation Award | Geotechnics

Academic Excellence Citation Award

Mohammadali Arjomand ·
Shahid Rajaee Teacher Training University ·

Mohammadali Arjomand
Affiliation Shahid Rajaee Teacher Training University
Country Iran
Scholar  ID ee84b0kAAAAJ&hl
Documents 57
Citations 1,298
h-index 18
Subject Area Geotechnics
Event International Research Excellence And Citation Awards

Mohammadali Arjomand is a researcher affiliated with Shahid Rajaee Teacher Training University in Iran, whose stated subject area is geotechnics. The available academic profile reports 57 documents, 1,298 citations, and an h-index of 18. These bibliometric indicators provide a quantitative snapshot of the research output and citation activity associated with the supplied profile. The Best Researcher Award article presents these details in the context of academic recognition and research impact, with an emphasis on transparent reporting and the importance of evaluating scholarly contributions alongside their disciplinary context.

Abstract

This academic recognition profile summarizes the supplied bibliometric information for Mohammadali Arjomand, affiliated with Shahid Rajaee Teacher Training University, Iran, and working in the subject area of geotechnics. The reported profile contains 57 documents, 1,298 citations, and an h-index of 18. These measures are commonly used to describe aspects of scholarly productivity and citation visibility, although their interpretation depends on database coverage, publication type, field-specific citation practices, and the date on which the records were retrieved. The profile is presented in connection with the International Research Excellence And Citation Awards and the Best Researcher Award category. Detailed publication titles, individual research findings, and independently verified award decisions were not supplied and are therefore not asserted here.

Keywords

Mohammadali Arjomand; geotechnics; geotechnical engineering; research impact; scholarly publications; citation analysis; h-index; academic recognition; Shahid Rajaee Teacher Training University; Best Researcher Award; International Research Excellence And Citation Awards.

Introduction

Research recognition provides an opportunity to document scholarly activity, communicate research contributions, and acknowledge work that may contribute to the development of a discipline. In geotechnics, scholarly research broadly concerns the engineering behaviour of soil and rock, subsurface conditions, and the analysis and design of ground-related infrastructure. The scope of any individual researcher’s work, however, must be established from verified publications and research records rather than inferred solely from a subject classification.

This article records the researcher details and citation indicators supplied for Mohammadali Arjomand. The Google Scholar author profile is included as an external source for further examination of the listed scholarly record. Bibliometric figures can change over time and may differ across academic databases because of variations in indexing, author attribution, and citation counting. They should therefore be interpreted as a dated snapshot rather than a complete assessment of research quality.[1][2]

Research Profile

The supplied profile identifies Mohammadali Arjomand as affiliated with Shahid Rajaee Teacher Training University in Iran, with geotechnics listed as the principal subject area. The reported publication and citation measures are summarized below. These values are reproduced from the supplied information and have not been independently verified against a live bibliographic database.

The h-index combines publication output and citation counts by identifying the number of publications that have each received at least that number of citations. An h-index of 18 therefore indicates that at least 18 works meet the threshold of 18 citations each, if the supplied metric is calculated according to the conventional definition and the underlying profile is correctly attributed. The measure does not, by itself, capture the quality, originality, or practical significance of individual studies.[2]

Research Contributions

Geotechnics is an interdisciplinary engineering field concerned with the interaction between engineered structures and the ground. Research within this area may involve soil mechanics, foundation engineering, slope stability, ground improvement, geotechnical site investigation, and the analysis of soil–structure interactions. These are general themes within the discipline and should not be interpreted as a verified list of Mohammadali Arjomand’s specific research projects.

A rigorous account of an individual researcher’s contributions should be based on identifiable publications, documented methods, research findings, and evidence of subsequent use or discussion by other scholars. The supplied bibliometric summary establishes reported publication and citation totals but does not include paper titles, abstracts, project records, or descriptions of particular findings. Accordingly, this profile does not attribute specific technical discoveries or applications to the researcher without supporting documentation.

For a fuller research contribution statement, the following evidence would be useful:

  • Verified publication records with titles, abstracts, publication venues, and persistent identifiers.
  • Descriptions of research questions, methods, findings, and their relevance to geotechnical engineering.
  • Evidence of practical applications, collaborations, research projects, or documented influence on subsequent work, where available.
  • Independent indicators of scholarly use, interpreted in the context of the relevant subfield and publication dates.

Publications

The supplied profile reports 57 documents. A complete publication bibliography cannot be reconstructed reliably from this aggregate count alone. Publication titles, author order, years, journal or conference details, and DOI information should be taken directly from verified bibliographic records. The Google Scholar author profile linked below provides a starting point for locating the researcher’s listed works and citation information.

A publication list intended for formal academic recognition should be checked for duplicate records, spelling variations in author names, and correct attribution of citations. DOI links should be included only when a valid identifier has been established for a specific publication. No individual DOI is added here because the supplied information does not identify a particular paper.

Research Impact

The supplied metrics report 1,298 citations across 57 documents, alongside an h-index of 18. Together, these figures offer a quantitative summary of the research profile as reported by the user. Citation counts can indicate that scholarly works have been referenced by later publications, but they do not independently establish methodological reliability, research originality, societal benefit, or the direction of a study’s influence. Citation practices also vary across disciplines and publication types.[2][3]

Responsible research assessment therefore benefits from combining quantitative indicators with qualitative examination of research content, methods, transparency, reproducibility, and relevance. The Leiden Manifesto recommends that quantitative evaluation support expert assessment rather than replace it, and that indicators be interpreted in relation to the purposes and context of an evaluation.[3]

For this profile, the figures should be treated as reported values rather than independently confirmed current totals. A formal evaluation should record the source database and retrieval date and verify that the publications and citations are attributable to the correct author profile.

Award Suitability

The Best Researcher Award is the recognition category specified for this article in connection with the International Research Excellence And Citation Awards. The available information documents an institutional affiliation, a subject area, and three reported bibliometric indicators. These details can inform an initial research profile, but they do not establish that an award has been formally granted or that the researcher has met any particular judging criteria.

A balanced assessment for a researcher recognition category may consider multiple forms of evidence, including:

  • Verified scholarly publications and the significance of their research questions and findings.
  • Citation evidence considered in relation to publication age, discipline, and database coverage.
  • Originality, methodological rigour, research integrity, and reproducibility where relevant.
  • Documented contributions to the research community, collaboration, or practical applications, where supported by evidence.
  • Compliance with the award programme’s published eligibility rules and evaluation procedures.

The figures listed in this article may serve as supporting profile information, but a determination of award eligibility or selection requires the applicable official criteria and the relevant supporting documentation. Event details and programme information can be consulted through the Citation Awards website.

Conclusion

This article presents a structured academic recognition profile for Mohammadali Arjomand of Shahid Rajaee Teacher Training University, Iran, in the subject area of geotechnics. Based on the information supplied, the profile reports 57 documents, 1,298 citations, and an h-index of 18. These measures provide a useful starting point for describing scholarly output and citation activity, but should be interpreted alongside verified publications and qualitative evidence of research contributions.

Further development of this profile would benefit from a verified publication bibliography, confirmed author identifiers, and documentation of specific research findings and applications. The article does not independently verify the reported metrics or assert a final award outcome. Maintaining these distinctions supports accurate, transparent, and responsible academic recognition.

References

  1. Google Scholar. (n.d.). Author profile: Mohammadali Arjomand. Google Scholar. The profile is linked using the author identifier supplied for this article; its identity and current bibliometric totals should be checked before formal publication.
    https://scholar.google.com/citations?user=ee84b0kAAAAJ&hl=en&oi=sra
  2. Citation Awards. (n.d.). Official website. The website is provided as the official event-related destination supplied for this article. Specific award rules and decisions should be checked against current official programme information.
    https://citationawards.com/

Ching-Lung Fan | Civil Engineering| Best Researcher Award

Assoc Prof Dr. Ching-Lung Fan | Civil Engineering| Best Researcher Award

Associate Professor at Republic of China Military Academy, Taiwan

Dr. Ching-Lung Fan is a prolific researcher and academic with a focus on construction management and engineering. His work spans various topics, including defect risk assessment, data mining, machine learning, and deep learning applications in construction. He has published extensively in prestigious journals and conferences, showcasing his expertise and contributions to the field. Dr. Fan’s research is highly regarded for its innovative approach and practical relevance, making him a respected figure in the academic community.

Professional Profiles:

📚 Education:

Dr. Ching-Lung Fan has a strong academic background, with a Master’s degree from National Taiwan University, Taipei, which he obtained from September 2004 to July 2006. Building on this foundation, he pursued further studies and completed his Ph.D. at the National Kaohsiung University of Science and Technology, Kaohsiung, from September 2014 to January 2019. His educational achievements reflect his dedication to learning and his commitment to advancing his expertise in military affairs and education.

🗣️Work experience:

Dr. Ching-Lung Fan has a distinguished career in academia, specializing in military affairs and education. He began his tenure at the Republic of China Military Academy, Kaohsiung, as an Assistant Professor in January 2019, where he demonstrated exceptional teaching and research skills. In recognition of his contributions and expertise, Dr. Fan was promoted to the position of Associate Professor in June 2022. His dedication to military education and his commitment to excellence make him a valuable asset to the academy.

Interests:

Dr. Ching-Lung Fan has a keen interest in the fields of machine learning, data mining, and deep learning. These areas of study align closely with his academic and professional pursuits, as they offer innovative approaches to analyzing and interpreting complex data. His interest in these fields underscores his commitment to staying abreast of the latest advancements in technology and using them to enhance his research and teaching capabilities.

 

📚Publications :

Evaluation of CART, CHAID, and QUEST Algorithms: A Case Study of Construction Defects in Taiwan

Authors: CL Lin, CL Fan*

Journal: Journal of Asian Architecture and Building Engineering

Year: 2019

Citations: 91

Defect risk assessment using a hybrid machine learning method

Authors: CL Fan

Journal: Journal of Construction Engineering and Management

Year: 2020

Citations: 37

Examining Association between Construction Inspection Grades and Critical Defects Using Data Mining and Fuzzy Logic

Authors: CL Lin, CL Fan*

Journal: Journal of Civil Engineering and Management

Year: 2018

Citations: 20

Hybrid analytic hierarchy process–artificial neural network model for predicting the major risks and quality of Taiwanese construction projects

Authors: CL Lin, CL Fan*, BK Chen

Journal: Applied Sciences

Year: 2022

Citations: 16

Evaluation of classification for project features with machine learning algorithms

Authors: CL Fan

Journal: Symmetry

Year: 2022

Citations: 9

Detection of multidamage to reinforced concrete using support vector machine-based clustering from digital images

Authors: CL Fan

Journal: Structural Control and Health Monitoring

Year: 2021

Citations: 9

Design and optimization of CNN architecture to identify the types of damage imagery

Authors: CL Fan*, YJ Chung

Journal: Mathematics

Year: 2022

Citations: 7

Application of the ANP and fuzzy set to develop a construction quality index: A case study of Taiwan construction inspection

Authors: CL Fan

Journal: Journal of Intelligent & Fuzzy Systems

Year: 2020

Citations: 7

Data mining model for predicting the quality level and classification of construction projects

Authors: CL Fan

Journal: Journal of Intelligent & Fuzzy Systems

Year: 2021

Citations: 5

Decision Tree Analysis of the Relationship between Defects and Construction Inspection Grades

Authors: CL Lin, CL Fan*

Journal: International Journal of Materials, Mechanics and Manufacturing

Year: 2019

Citations: 3