Siphokazi ngcinela | Agricultural Data Analysis | Best Researcher Award

Published on by Research Data Analysis

Best Researcher Award

Siphokazi ngcinela – University of South Africa – Unisa Science Campus

Siphokazi ngcinela
Affiliation University of South Africa – Unisa Science Campus
Country South Africa
Scopus ID 57207996206
Documents 3
Citations 12
h-index 1
Subject Area Agricultural Data Analysis
Event International Research Data Analysis Excellence & Awards
ORCID 0000-0001-5138-4487

Siphokazi ngcinela is affiliated with the University of South Africa – Unisa Science Campus and is associated with research activity in Agricultural Data Analysis. The available bibliometric information identifies a Scopus author record containing three indexed documents, twelve citations, and an h-index of one, providing a concise basis for scholarly profile assessment. [1]

Abstract

This article presents an academic recognition profile of Siphokazi ngcinela, affiliated with the University of South Africa – Unisa Science Campus. The profile considers available bibliometric indicators, research orientation in Agricultural Data Analysis, publication activity, and potential relevance to the International Research Data Analysis Excellence & Awards. [2]

Keywords

Agricultural Data Analysis; bibliometrics; research evaluation; scholarly publications; Scopus; ORCID; research impact; academic recognition; South Africa; data-driven research. [1]

Introduction

Agricultural Data Analysis supports evidence-based investigation by applying analytical approaches to agricultural information, research observations, and measurable outcomes. Siphokazi ngcinela’s available scholarly identifiers and indexed record provide a documented basis for reviewing research activity, publication visibility, and academic contribution within this broad interdisciplinary area. [3]

Research Profile

The available research profile identifies Siphokazi ngcinela with the University of South Africa – Unisa Science Campus in South Africa. The associated Scopus author record lists three documents, twelve citations, and an h-index of one, while the ORCID identifier provides an additional persistent scholarly identity. [2]

Research Contributions

Available profile information indicates scholarly activity connected with Agricultural Data Analysis. Research contributions in this area may involve the systematic interpretation of agricultural datasets, analytical evaluation of research evidence, and communication of findings through scholarly outputs. The available indexed record documents participation in formal research dissemination. [3]

Publications

The Scopus author information associated with Siphokazi ngcinela records three indexed documents. These publications constitute the currently available bibliometric evidence for assessing publication activity. Specific publication titles, journal details, and DOI metadata should be verified directly through the linked Scopus record and associated publication pages. [1]

Research Impact

The available Scopus metrics report twelve citations and an h-index of one. These indicators provide a limited quantitative perspective on the visibility and use of indexed publications. Bibliometric measures should be interpreted alongside disciplinary context, publication age, research scope, collaboration patterns, and qualitative evidence of contribution. [2]

Award Suitability

The documented affiliation, persistent researcher identifier, indexed publications, and measurable citation record provide relevant information for consideration within the International Research Data Analysis Excellence & Awards. Award suitability may be assessed through a balanced review of scholarly outputs, research relevance, methodological contribution, and the event’s established evaluation criteria. [3]

Conclusion

Siphokazi ngcinela’s available academic profile presents documented affiliation with the University of South Africa – Unisa Science Campus, supported by Scopus and ORCID identifiers. The indexed publication and citation record offers a measurable foundation for academic review, while additional qualitative assessment can provide broader context for recognition. [2]

References

  1. Mapping the Land Use Changes in Cultivation Areas of Maize and Soybean from 2006 to 2017 in the North West and Free State Provinces, South Africa.
    https://www.mdpi.com/2073-4395/14/5/1002
  2. Does farm location matter? Assessing emerging farmers’ climate change awareness in South Africa.
    https://www.sciencedirect.com/org/science/article/abs/pii/S030682932500062X
  3. Elsevier. (n.d.). Scopus author details: Siphokazi ngcinela, Author ID 57207996206. Scopus..
    https://www.scopus.com/pages/authors/57207996206

Christian Schachtner | Knowledge Management | Innovative Research Award

Published on by Research Data Analysis

Innovative Research Award

Christian Schachtner — Hochschule RheinMain, Germany

Christian Schachtner
Affiliation Hochschule RheinMain
Country Germany
Scopus ID 58199741900
Documents 28
Citations 14
h-index 3
Subject Area Knowledge Management
Event International Research Data Analysis Excellence & Awards
ORCID 0000-0001-5332-6280

Christian Schachtner is affiliated with Hochschule RheinMain in Germany and is associated with research in the area of knowledge management. The available bibliographic profile records 28 documents, 14 citations, and an h-index of 3. These indicators provide a concise bibliometric basis for considering the researcher within an academic recognition framework.[1]

Abstract

This article presents an academic recognition profile of Christian Schachtner, Hochschule RheinMain, Germany, with emphasis on knowledge management and documented bibliometric indicators. The profile records 28 documents, 14 citations, and an h-index of 3. The information provides a structured basis for assessing research activity, scholarly visibility, and potential award suitability.[1]

Keywords

Knowledge management; research analytics; bibliometrics; scholarly publications; citation analysis; research impact; academic recognition; Hochschule RheinMain; Scopus; ORCID.

 Introduction

Knowledge management research examines how organizations create, organize, share, and apply knowledge to support learning and informed decision-making. Christian Schachtner’s profile is situated within this broad field, with bibliographic evidence indicating an established publication record. The available Scopus information provides a quantitative reference point for reviewing his scholarly activity and recognition potential.[2]

Research Profile

Christian Schachtner is affiliated with Hochschule RheinMain, Germany, and is identified in the supplied profile as a researcher in Knowledge Management. His Scopus author record contains 28 documents, 14 citations, and an h-index of 3. His ORCID identifier provides an additional persistent mechanism for distinguishing his scholarly record and research activities.[2]

Research Contributions

The documented contribution profile can be assessed through publication volume, citation activity, and subject-area alignment. Twenty-eight indexed documents indicate sustained scholarly output, while fourteen citations and an h-index of three provide measurable evidence of subsequent scholarly use. These indicators should be interpreted as bibliometric measures rather than comprehensive measures of research quality or societal contribution.[3]

Publications

The available Scopus profile reports 28 documents associated with the researcher. This publication count indicates a substantive indexed output within the available bibliographic record. Individual publication titles, journals, publication years, co-authorship patterns, and DOI information should be verified directly against the relevant bibliographic records before being used for detailed publication-level assessment.[1]

Research Impact

Research impact may be considered through several complementary indicators, including citations, h-index, publication continuity, and evidence of knowledge transfer. The profile records 14 citations and an h-index of 3, demonstrating measurable scholarly visibility in the indexed record. A balanced evaluation should combine these quantitative indicators with qualitative evidence concerning relevance, originality, and practical contribution.[3]

Award Suitability

The documented profile presents several indicators relevant to academic recognition, including 28 indexed documents, 14 citations, an h-index of 3, and a stated specialization in Knowledge Management. These measures support consideration within a research recognition process, while final award suitability should also account for originality, research quality, methodological contribution, relevance, and independently verifiable evidence beyond bibliometric counts.[1]

Conclusion

Christian Schachtner’s available academic profile reflects a documented research presence at Hochschule RheinMain in the field of Knowledge Management. The reported 28 documents, 14 citations, and h-index of 3 provide a concise quantitative foundation for academic assessment. Further evaluation can strengthen the recognition process by incorporating publication quality, research originality, collaboration, and demonstrated influence.[2]

 References

  1. Accompanying study of the development process towards a smart city strategy-with a particular focus on social change.
    https://www.researchgate.net/publication/378272819_Accompanying_study_of_the_development_process_towards_a_smart_city_strategy-with_a_particular_focus_on_social_change
  2. University Transfer Architectures for Smart Governance: A Regional Comparison of Scientific Community Building.
    https://www.mdpi.com/2076-3387/16/7/323
  3. User-Generated Content in Citizen Service Platforms. Proceedings of the National Academy of Sciences, 102
    https://link.springer.com/rwe/10.1007/978-3-658-46709-8_12-1

Any Rufaedah | Social Psychology | Best Researcher Award

Published on by Research Data Analysis

Best Researcher Award

Any Rufaedah – Universitas Nahdlatul Ulama Indonesia

Any Rufaedah
Affiliation Universitas Nahdlatul Ulama Indonesia
Country Indonesia
Scopus ID 57202058470
Documents 13
Citations 118
h-index 6
Subject Area Social Psychology
Event International Research Data Analysis Excellence & Awards
ORCID 0000-0001-6966-1796

Any Rufaedah is a researcher affiliated with Universitas Nahdlatul Ulama Indonesia whose documented scholarly profile is associated with the subject area of Social Psychology. Available bibliographic information records 13 documents, 118 citations, and an h-index of 6, providing a quantitative basis for academic recognition. [1]

Abstract

This article presents a concise academic recognition profile of Any Rufaedah, affiliated with Universitas Nahdlatul Ulama Indonesia. The available Scopus record identifies 13 documents, 118 citations, and an h-index of 6 within Social Psychology. These bibliometric indicators provide a structured basis for describing research activity, visibility, scholarly contribution, and award suitability. [1]

Keywords

  • Any Rufaedah
  • Best Researcher Award
  • Social Psychology
  • Research Impact
  • Bibliometric Indicators
  • Scholarly Publications
  • International Research Data Analysis Excellence & Awards

Introduction

Academic recognition increasingly considers transparent evidence of scholarly productivity, citation visibility, and sustained research activity. Any Rufaedah’s indexed profile records 13 documents, 118 citations, and an h-index of 6, offering measurable indicators of scholarly presence. These data support an objective overview while acknowledging that bibliometric measures represent only one dimension of research quality. [1]

Research Profile

Any Rufaedah is affiliated with Universitas Nahdlatul Ulama Indonesia in Indonesia and is associated with Social Psychology. The available researcher identifiers include Scopus Author ID 57202058470 and ORCID 0000-0001-6966-1796. Together, these identifiers facilitate scholarly attribution, profile verification, and distinction between researchers across bibliographic and researcher-information systems. [2]

Research Contributions

The documented research contribution can be considered through publication activity and citation performance. Thirteen indexed documents indicate an established body of scholarly output, while 118 citations suggest measurable use of the researcher’s work within the indexed literature. The h-index of 6 further provides a standardized indicator of citation distribution across publications. [1]

Publications

The Scopus profile reports 13 documents associated with Any Rufaedah. These indexed publications constitute the available bibliographic basis for assessing research productivity in this profile. Specific article titles, journal details, publication years, and DOI identifiers were not supplied in the input data; therefore, individual publications and DOI records are not asserted beyond the documented Scopus publication count. [3]

 Research Impact

Research impact is reflected in the available citation indicators, with 118 citations recorded for the researcher’s indexed documents. An h-index of 6 indicates that at least six publications have each received six or more citations under the applicable database record. These indicators provide quantitative evidence of scholarly visibility without independently establishing broader societal or practical impact. [2]

Award Suitability

The available bibliometric record provides relevant evidence for consideration for a Best Researcher Award within the International Research Data Analysis Excellence & Awards framework. The combination of 13 documents, 118 citations, and an h-index of 6 demonstrates measurable scholarly activity. Final recognition should additionally consider research quality, originality, contribution, and eligibility requirements. [3]

Conclusion

Any Rufaedah’s available academic profile presents a measurable record of scholarly productivity and citation visibility in Social Psychology. The documented Scopus indicators—13 documents, 118 citations, and an h-index of 6—provide a concise quantitative foundation for academic recognition. These measures should be interpreted alongside qualitative evidence when determining overall research distinction. [1]

References

  1. “Theologization” of Psychology and “Psychologization” of Religion: How Do Psychology and Religion Supposedly Contribute to Prevent and Overcome Social Conflicts.
    https://www.sciencedirect.com/science/article/pii/S1878029614000656
  2. Increasing integrative complexity on convicted terrorists in Indonesia.
    https://www.researchgate.net/publication/326578700_Increasing_integrative_complexity_on_convicted_terrorists_in_Indonesia
  3. Influence of Five Types of Ecological Attachments on General Pro-environmental Behavior.
    https://www.sciencedirect.com/science/article/pii/S1877042813025093

VASSILIOS ROTHOS | Nonlinear Waves | Excellence in Research

Published on by Research Data Analysis

 

Excellence in Research

Vassilios Rothos – Aristotle University of Thessaloniki, Greece

Vassilios Rothos
Affiliation Aristotle University of Thessaloniki
Country Greece
Scopus ID 6602556662
Documents 55
Citations 639
h-index 15
Subject Area Nonlinear Waves
Event International Research Data Analysis Excellence & Awards
ORCID 0000-0003-3354-1615

Vassilios Rothos is a researcher affiliated with Aristotle University of Thessaloniki, Greece, whose indexed scholarly record is associated with the subject area of nonlinear waves. The available bibliometric information records 55 documents, 639 citations, and an h-index of 15, providing a quantitative basis for considering research visibility and scholarly influence. [1]

Abstract

This article presents a concise academic recognition profile of Vassilios Rothos, affiliated with Aristotle University of Thessaloniki, Greece. The profile focuses on his indexed research record, scholarly output, citation performance, h-index, subject-area association with nonlinear waves, and relevance to research-data-driven academic evaluation. The documented metrics provide a structured basis for assessing scholarly visibility. [1]

Keywords

  • Vassilios Rothos
  • Nonlinear Waves
  • Research Data Analysis
  • Scholarly Impact
  • Bibliometrics
  • Citation Analysis
  • Research Excellence

Introduction

Research assessment increasingly combines publication records, citation indicators, and subject-specific evidence to describe scholarly performance. In nonlinear-wave research, quantitative analysis supports the interpretation of complex physical phenomena and mathematical models. Rothos’s indexed record provides measurable indicators for examining research activity and visibility within an established scholarly information environment. [2]

Research Profile

The available profile identifies Vassilios Rothos with Aristotle University of Thessaloniki and associates his research with nonlinear waves. His Scopus record contains 55 documents, 639 citations, and an h-index of 15. His ORCID identifier provides an additional persistent scholarly identity mechanism that supports researcher record identification and disambiguation. [3]

Research Contributions

The research profile can be considered within the broader study of nonlinear-wave phenomena, where analytical, computational, and quantitative approaches are used to investigate propagation, interaction, stability, and related dynamics. The documented publication and citation record indicates sustained scholarly activity, while subject-area classification provides a focused context for interpreting the researcher’s academic contribution. [2]

Publications

The indexed record reports 55 documents associated with the researcher. Such records may encompass journal articles and other indexed scholarly outputs, although individual publication titles and document types are not specified in the supplied profile. Publication quantity therefore provides evidence of documented research activity, while bibliographic verification remains necessary for detailed publication-level assessment. [1]

 Research Impact

The recorded 639 citations and h-index of 15 provide quantitative indicators of scholarly visibility and citation-based influence. These measures are useful for structured evaluation but should be interpreted alongside field, career stage, publication patterns, collaboration, and citation practices. The indicators therefore support, rather than independently determine, an assessment of research impact. [2]

 Award Suitability

The documented research profile presents measurable scholarly activity, citation visibility, and a defined subject-area association with nonlinear waves. These characteristics are relevant to an award framework emphasizing research data, publication performance, and academic impact. Final recognition should nevertheless consider verified publication evidence, originality, methodological contribution, and the specific evaluation criteria of the International Research Data Analysis Excellence & Awards. [3]

Conclusion

Vassilios Rothos’s available scholarly profile demonstrates a documented record of research activity within nonlinear waves. The combination of 55 documents, 639 citations, and an h-index of 15 offers a quantitative foundation for academic recognition. A complete evaluation should integrate these indicators with verified research quality, originality, contribution, and disciplinary context. [1]

References

  1. Adiabatic perturbation theory for the F = 1 spinor nonlinear Schrödinger equation with nonvanishing boundary conditions.
    https://www.researchgate.net/publication/408289058_Adiabatic_perturbation_theory_for_the_F_1_spinor_nonlinear_Schrodinger_equation_with_nonvanishing_boundary_conditions
  2. Spectral Stability of Travelling Waves in a δ-Regularized Dissipative Sine-Gordon Equation.
    https://www.mdpi.com/2073-8994/18/3/512
  3. Travelling Waves in Hamiltonian Systems on 2D Lattices with Nearest Neighbor Interactions.
    https://www.researchgate.net/publication/386730082_Travelling_Waves_in_Hamiltonian_Systems_on_2D_Lattices_with_Nearest_Neighbor_Interactions

Yingjie Yang | Data Science | Best Researcher Award

Published on by Research Data Analysis

Best Researcher Award

Yingjie Yang – De Montfort University

Yingjie Yang
Affiliation De Montfort University
Country United Kingdom
Scopus ID 7409384730
Documents 236
Citations 5720
h-index 38
Subject Area Data Science
Event International Research Data Analysis Excellence & Awards
ORCID 0000-0003-4525-5624

Yingjie Yang is a researcher affiliated with De Montfort University whose scholarly profile is associated with Data Science and interdisciplinary research involving data-driven methods. The available Scopus indicators record 236 documents, 5720 citations and an h-index of 38, providing a quantitative basis for assessing publication activity and scholarly influence in relation to the Best Researcher Award. [1]

Abstract

This article presents an academic recognition profile of Yingjie Yang, affiliated with De Montfort University, for consideration under the Best Researcher Award. Available bibliometric indicators, including 236 documents, 5720 citations and an h-index of 38, are considered alongside research activity in Data Science and related scholarly contributions. [1]

Keywords

Best Researcher Award; Yingjie Yang; De Montfort University; Data Science; Research Data Analysis; Bibliometric Assessment; Scholarly Publications; Citation Impact; Research Excellence; Academic Recognition. [2]

Introduction

Academic recognition commonly considers research productivity, citation performance, publication continuity and contribution to a specialist field. Yingjie Yang’s available scholarly indicators provide a measurable profile for examining research achievement within Data Science. Such evaluation supports transparent comparison of documented academic output and influence using established bibliometric information. [3]

Research Profile

Yingjie Yang is affiliated with De Montfort University in the United Kingdom and is associated with research in Data Science. The available Scopus profile records 236 documents, 5720 citations and an h-index of 38. These indicators collectively describe sustained scholarly activity and a documented record of academic visibility. [1]

Research Contributions

The research profile demonstrates contributions represented through a substantial body of indexed scholarly documents. Within the Data Science context, such work contributes to the continuing development, application and evaluation of data-driven knowledge. The accumulated publication record also indicates engagement with research communication and dissemination across relevant academic channels. [1]

Publications

The available Scopus record lists 236 documents associated with the researcher profile, indicating sustained publication activity. Indexed publications provide an important basis for evaluating scholarly productivity because they document research dissemination and enable subsequent citation analysis. Specific publication details should be interpreted through the linked author profile and corresponding publisher records.[2]

Research Impact

The profile records 5720 citations and an h-index of 38, indicating that the published work has received measurable scholarly attention. Citation indicators are not complete measures of research quality, but they provide useful evidence of academic visibility and uptake. Their interpretation is strengthened when considered with disciplinary context and documented research outputs. [3]

Award Suitability

Based on the available publication and citation indicators, Yingjie Yang presents a documented academic profile relevant to consideration for the Best Researcher Award. The combination of publication volume, citation performance and an h-index of 38 provides objective evidence for assessment. Final recognition should remain subject to the event’s eligibility criteria and review process. [1]

Conclusion

The available research profile of Yingjie Yang reflects sustained scholarly publication activity and measurable citation impact in association with Data Science. With 236 documents, 5720 citations and an h-index of 38, the profile provides evidence suitable for structured academic evaluation. These documented indicators support informed consideration for research recognition. [1]

 References

  1. Predicting the number of care beds for older people by a novel grey Verhulst cosine self-memory model: two case studies of Jiangsu and Shanghai, China.
    https://link.springer.com/article/10.1186/s12877-026-07337-6
  2. Interpretable Temporal Graph Attention Network and Cross-Modal Fusion for Early Rumor Detection.
    https://www.researchgate.net/publication/405011816_Interpretable_Temporal_Graph_Attention_Network_and_Cross-Modal_Fusion_for_Early_Rumor_Detection
  3. A novel time-varying Wiener process for adaptive RUL prediction under multiple uncertainties
    https://www.researchgate.net/publication/401712852_A_novel_time-varying_Wiener_process_for_adaptive_RUL_prediction_under_multiple_uncertainties

Omar H. Abd Elkade | Utilities Analytics | Best Researcher Award

Published on by Research Data Analysis

Best Researcher Award

Omar H. Abd Elkade
Researcher Omar H. Abd Elkade
Affiliation King Saud University
Country Saudi Arabia
Scopus ID 57192277362
Documents 7
Citations 65
h-index 4
Subject Area Utilities Analytics
Event International Research Data Analysis Excellence & Awards
ORCID 0000-0002-7351-813X

Omar H. Abd Elkade – King Saud University

Omar H. Abd Elkade is affiliated with King Saud University, Saudi Arabia, and is represented in the supplied researcher information by a Scopus author record containing seven documents, 65 citations, and an h-index of 4. The profile is considered in the context of the International Research Data Analysis Excellence & Awards and the stated subject area of Utilities Analytics.[1]

Abstract

This academic recognition profile presents the supplied bibliometric information for Omar H. Abd Elkade, affiliated with King Saud University. The documented record reports seven publications, 65 citations, and an h-index of 4. The profile is examined within Utilities Analytics and the International Research Data Analysis Excellence & Awards framework.[1]

Keywords

Keywords: Omar H. Abd Elkade; King Saud University; Utilities Analytics; research data analysis; bibliometrics; Scopus; citation impact; h-index; research recognition; Best Researcher Award.

 Introduction

Research recognition commonly considers documented scholarly outputs, citation activity, disciplinary relevance, and researcher visibility. Omar H. Abd Elkade is presented here through supplied bibliometric indicators associated with King Saud University and Utilities Analytics. These indicators provide a structured basis for describing research activity without extending conclusions beyond the available profile evidence.[1]

 Research Profile

The available research profile identifies Omar H. Abd Elkade with King Saud University in Saudi Arabia and associates the record with Utilities Analytics. The supplied Scopus information reports seven documents, 65 citations, and an h-index of 4. ORCID provides a persistent researcher identifier that can support scholarly identity and record discovery. [2]

Research Contributions

Based on the supplied information, the principal documented contribution is an identifiable scholarly record within the stated Utilities Analytics subject area. Seven indexed documents and 65 citations indicate measurable research dissemination and scholarly attention. However, specific methodological innovations, datasets, collaborations, or individual project contributions require verification from the underlying publications and institutional records.[1]

 Publications

The supplied bibliometric record lists seven documents associated with Scopus author ID 57192277362. These documents constitute the available publication-count evidence for this profile. Individual article titles, journals, publication years, co-authorship patterns, and article-level DOI information were not supplied and therefore are not attributed here without verification from the corresponding scholarly records.[2]

Research Impact

The reported 65 citations and h-index of 4 provide quantitative indicators of scholarly visibility within the supplied Scopus record. Citation counts can assist comparative assessment but should be interpreted alongside publication age, field norms, authorship, venue, and research context. The available figures therefore document impact indicators rather than establishing broader societal or technological impact.[3]

Award Suitability

The supplied record provides several measurable criteria relevant to research recognition: an identifiable institutional affiliation, seven indexed documents, 65 citations, an h-index of 4, and a stated connection with Utilities Analytics. These indicators support consideration for a research award, while final suitability should depend on the award’s official eligibility criteria and independent verification of the submitted evidence. [3]

Conclusion

Omar H. Abd Elkade’s supplied academic profile demonstrates a documented research record associated with King Saud University and Utilities Analytics. The reported seven documents, 65 citations, and h-index of 4 provide concise bibliometric evidence for research activity. Further evaluation should incorporate verified publication quality, research contributions, disciplinary context, and the award’s formal assessment criteria.[1]

References

  1. Mineral analysis of Pistacia species with inductively coupled plasma-mass spectrometry (ICP-MS).
    https://www.researchgate.net/publication/390168549_Mineral_analysis_of_Pistacia_species_with_inductively_coupled_plasma-mass_spectrometry_ICP-MS
  2. Resveratrol and Neuroprotection: Impact and Its Therapeutic Potential in Alzheimer’s Disease.
    https://pmc.ncbi.nlm.nih.gov/articles/PMC7804889/
  3. Chemical activation of calcium aluminate cement composites cured at elevated temperature
    https://www.researchgate.net/publication/233379459_Chemical_activation_of_calcium_aluminate_cement_composites_cured_at_elevated_temperature

Hatem Abuelizz | Quantitative Research | Best Researcher Award

Published on by Research Data Analysis

Best Researcher Award

Hatem Abuelizz — King Saud University, Saudi Arabia

Hatem Abuelizz
Affiliation King Saud University
Country Saudi Arabia
Scopus ID 56667652300
Documents 149
Citations 2,037
h-index 24
Subject Area Quantitative Research
Event International Research Data Analysis Excellence & Awards
ORCID 0000-0002-7092-7544

Hatem Abuelizz is a researcher affiliated with King Saud University whose indexed scholarly record comprises 149 documents, 2,037 citations, and an h-index of 24. These bibliometric indicators provide a quantitative basis for considering research productivity, scholarly visibility, and citation influence within the context of the International Research Data Analysis Excellence & Awards.[1]

Abstract

This academic recognition profile presents Hatem Abuelizz in relation to the Best Researcher Award within the International Research Data Analysis Excellence & Awards. The assessment emphasizes quantitative indicators, including publication volume, citation count, and h-index, while positioning these measures within a broader framework of research productivity, scholarly visibility, and data-oriented research evaluation.[1]

Keywords

  • Quantitative Research
  • Research Data Analysis
  • Bibliometric Evaluation
  • Research Productivity
  • Citation Impact
  • h-index
  • Scholarly Research
  • Research Excellence

Introduction

Quantitative research applies numerical measurement, statistical methods, and structured datasets to investigate research questions objectively. Within research data analysis, quantitative indicators can support systematic assessment of productivity and scholarly influence. Hatem Abuelizz’s indexed record provides measurable evidence that can be considered when evaluating research performance for an international recognition program.[1]

Research Profile

Hatem Abuelizz is affiliated with King Saud University in Saudi Arabia. The supplied Scopus information identifies 149 documents, 2,037 citations, and an h-index of 24. His ORCID record provides a persistent researcher identifier, while Scopus supplies an indexed bibliometric profile useful for structured quantitative research evaluation and scholarly record verification.[1][2]

Research Contributions

The documented research record indicates sustained scholarly activity measured through indexed publications and citation accumulation. A portfolio of 149 documents represents substantial publication activity, while 2,037 citations and an h-index of 24 provide complementary quantitative indicators. These measures can assist reviewers in examining research productivity, influence, continuity, and visibility across scholarly outputs.[1]

Publications

The supplied Scopus profile records 149 documents associated with Hatem Abuelizz. This publication count provides a quantitative measure of documented scholarly output, although publication totals alone do not establish research quality. Detailed assessment should additionally consider article relevance, methodological rigor, venue quality, collaboration, citation distribution, and individual contribution to published research.[1]

Research Impact

Research impact can be examined through multiple complementary indicators. The reported 2,037 citations reflect accumulated scholarly attention, while an h-index of 24 indicates repeated citation performance across a substantial portion of the publication record. Together, these measures provide quantitative evidence of visibility and influence that can inform comparative research assessment.[1]

Award Suitability

For the International Research Data Analysis Excellence & Awards, the documented publication and citation indicators provide relevant quantitative evidence for evaluating research achievement. The combination of 149 documents, 2,037 citations, and an h-index of 24 demonstrates a substantial indexed scholarly record. Final award suitability should also incorporate qualitative review and field-specific evidence.[1][3]

Conclusion

Hatem Abuelizz presents a measurable scholarly profile relevant to quantitative research evaluation. The reported publication count, citation total, and h-index establish a substantial bibliometric record for consideration in the Best Researcher Award. These indicators support structured assessment while recognizing that comprehensive evaluation should combine quantitative evidence with research quality, relevance, originality, and contribution.[1][2]

References

  1. Synthesis and anticancer activity of new quinazoline derivatives.
    https://www.researchgate.net/publication/316360785_Synthesis_and_anticancer_activity_of_new_quinazoline_derivatives
  2. Experimental and theoretical evaluation of eco-friendly of pyrhazole-amide conjugates on the corrosion inhibition performance for mild steel in 1 M HCl solution.
    https://www.researchgate.net/publication/395361917_Experimental_and_theoretical_evaluation_of_eco-friendly_of_pyrhazole-amide_conjugates_on_the_corrosion_inhibition_performance_for_mild_steel_in_1_M_HCl_solution
  3. An in-depth study of indolone derivatives as potential lung cancer treatment
    https://www.researchgate.net/publication/388072633_An_in-depth_study_of_indolone_derivatives_as_potential_lung_cancer_treatment

Alexander Salkazanov | Quantum Technologies | Best Researcher Award

Published on by Research Data Analysis

Best Researcher Award

Alexander Salkazanov — National Research Nuclear University Moscow Engineering Physics Institute, Russia

Researcher Information
Affiliation National Research Nuclear University Moscow Engineering Physics Institute
Country Russia
Scopus ID 58078232000
Documents 6
Citations 12
h-index 3
Subject Area Quantum technologies
Event International Research Data Analysis Excellence & Awards
ORCID 0000-0002-0210-7464

Alexander Salkazanov is presented in this academic recognition profile as a researcher associated with quantum technologies and affiliated with the National Research Nuclear University Moscow Engineering Physics Institute. The supplied bibliographic indicators include six documents, twelve citations, and an h-index of three, providing a concise overview of the stated research record. [1]

Abstract

This profile documents the stated academic recognition of Alexander Salkazanov in the field of quantum technologies. His supplied research record comprises six documents, twelve citations, and an h-index of three. The profile emphasizes bibliographic identification, research orientation, publication activity, and potential relevance to an international research excellence award. [1]

Keywords

  • Quantum technologies
  • Quantum research
  • Quantum information
  • Research excellence
  • Scientific publications
  • Research impact

Introduction

Quantum technologies combine principles of quantum mechanics with information processing, measurement, communication, and computation. Their development has created interdisciplinary research directions spanning physics, mathematics, computer science, and engineering. Contemporary scholarship emphasizes scalable architectures, reliable control, quantum information processing, and practical applications, establishing a broad framework for evaluating researchers working in this rapidly developing field. [2]

Research Profile

The supplied profile identifies Alexander Salkazanov with the National Research Nuclear University Moscow Engineering Physics Institute and associates his subject area with quantum technologies. Bibliographic information supplied for this article records six documents, twelve citations, and an h-index of three. These indicators provide a structured snapshot of the stated scholarly record. [1]

Research Contributions

Research contributions in quantum technologies may encompass theoretical models, experimental methods, computational approaches, quantum information processing, sensing, communication, and emerging technological applications. On the supplied evidence, Salkazanov is categorized within this subject area, while detailed contribution claims should be evaluated against individual publications, methodologies, datasets, and documented research outputs before assigning specific technical achievements. [1]

Publications

The supplied bibliographic record indicates six documents associated with the researcher. Publication-level assessment should consider authorship, venue, methodology, citations, research novelty, and relevance to quantum technologies. Because individual publication titles and DOI identifiers were not supplied, this article does not attribute specific papers or findings to Salkazanov beyond the stated bibliographic indicators. [1]

Research Impact

Research impact in quantum technologies can be assessed through scholarly citations, subsequent research use, technical adoption, collaboration, intellectual property, and broader scientific or industrial influence. The supplied profile reports twelve citations and an h-index of three, which provide quantitative bibliographic indicators but should be interpreted alongside publication quality, field norms, and research context. [1]

Award Suitability

The stated association with quantum technologies makes the researcher potentially relevant to recognition focused on scientific research and emerging technology. Suitability for an award should ultimately depend on independently documented achievements, originality, publication quality, research impact, and alignment with the award criteria. Bibliographic indicators can support assessment but should not alone determine recognition. [1]

Conclusion

Alexander Salkazanov is presented as a researcher associated with quantum technologies and the National Research Nuclear University Moscow Engineering Physics Institute. The supplied record identifies six documents, twelve citations, and an h-index of three. Further evaluation of research significance should examine primary publications, technical contributions, collaboration, and independently verifiable evidence of impact. [1]

11. References

    1. Elsevier. (n.d.). Scopus author details: Alexander Salkazanov, Author ID 58078232000. Scopus.
      https://www.scopus.com/authid/detail.uri?authorId=58078232000
    2. Investigation of the Energy Levels of the Kramers Degenerate 14NV-13C System in a Magnetic and Electric Field
      https://link.springer.com/article/10.1134/S1063778825100357

Seid Mehammed Abdu | Machine Learning | Innovative Research Award

Published on by Research Data Analysis

Innovative Research Award

Seid Mehammed Abdu – Woldia University

Seid Mehammed Abdu is a researcher affiliated with Woldia University, Ethiopia, whose listed subject area is machine learning. His research profile is associated with computational and data-driven approaches relevant to contemporary research and innovation. This article presents a neutral academic overview of his available bibliometric information and award suitability.

Researcher Information
Affiliation Woldia University
Country Ethiopia
Scopus ID 60330160800
Documents 3
Citations 5
h-index 2
Subject Area Machine Learning
Event International Research Data Analysis Excellence & Awards
ORCID 0000-0002-5850-5947

Abstract

Seid Mehammed Abdu is affiliated with Woldia University in Ethiopia and is associated with the academic subject area of machine learning. The supplied bibliometric record lists three documents, five citations, and an h-index of two. This profile provides a concise basis for describing research activity and considering suitability for the Innovative Research Award within the International Research Data Analysis Excellence & Awards event. [1]

Keywords

  • Machine Learning
  • Data Analysis
  • Computational Research
  • Research Innovation
  • Bibliometrics
  • Academic Research

Introduction

Seid Mehammed Abdu is a researcher at Woldia University whose listed subject area is machine learning. His scholarly profile reflects research activity involving computational methods and data-driven analysis. The profile records three documents, five citations, and an h-index of two, providing a concise bibliometric view of his research record overall. [2]

Research Profile

Seid Mehammed Abdu is affiliated with Woldia University in Ethiopia and is identified in Scopus by Author ID 60330160800. His research classification includes machine learning, a field concerned with computational models that learn patterns from data. Available profile indicators include three documents, five citations, and an h-index of two currently. [1]

Research Contributions

The available bibliometric information indicates contributions within machine learning and related data-driven research. With three indexed documents and five citations, his record demonstrates scholarly dissemination. These indicators should be interpreted as descriptive measures rather than comprehensive assessments of research quality, because citation counts and indexing coverage vary across databases and disciplines. [3]

Publications

Abdu’s indexed publication record currently comprises three documents according to the supplied Scopus profile information. The available data establish publication activity but do not provide sufficient bibliographic details to characterize individual studies, methods, venues, or findings. For publication-level descriptions, readers should consult the author’s current Scopus record and associated DOI metadata. [2]

Research Impact

The supplied profile records five citations and an h-index of two, indicating that multiple publications have received scholarly citations within the indexed coverage available through Scopus. Bibliometric indicators provide useful evidence of research visibility, but they should be considered alongside publication quality, methodological contribution, collaboration, reproducibility, and broader practical influence. [1]

 Award Suitability

The Innovative Research Award recognizes scholarly work demonstrating meaningful research activity, originality, and potential contribution to a field. Abdu’s documented activity in machine learning, together with three indexed documents, five citations, and an h-index of two, provides relevant evidence for consideration, subject to the award’s formal eligibility criteria and supporting documentation. [3]

Conclusion

Seid Mehammed Abdu’s documented research profile places him within machine learning and identifies an active scholarly record at Woldia University. The supplied indicators provide a concise basis for academic recognition, while fuller assessment should consider individual publications, originality, methodological rigor, research significance, and verified supporting evidence beyond bibliometric measures alone. [2]

References

  1. PhishNet 1.0: optuna-optimized stacking ensemble with Boruta-based feature selection for phishing URL detection.
    https://www.researchgate.net/publication/398411516_PhishNet_10_optuna-optimized_stacking_ensemble_with_Boruta-based_feature_selection_for_phishing_URL_detection
  2. A lightweight deep learning and whale optimization framework for sustainable precision agriculture.
    https://link.springer.com/article/10.1007/s10791-026-09952-8
  3. Improving the Performance of Proof of Work-Based Bitcoin Mining Using CUDA.
    https://www.researchgate.net/publication/390200568_Improving_the_Performance_of_Proof_of_Work-Based_Bitcoin_Mining_Using_CUDA

Aneta Pobudkowska | Diagnostic Analytics | Best Researcher Award

Published on by Research Data Analysis

Best Researcher Award

Aneta Pobudkowska – Warsaw University of Technology
Academic Recognition
Researcher Aneta Pobudkowska
Affiliation Warsaw University of Technology
Country Poland
Scopus ID 6506665315
Documents 43
Citations 1,535
h-index 22
Subject Area Diagnostic Analytics
Event International Research Data Analysis Excellence & Awards
ORCID 0000-0002-1020-618X

Aneta Pobudkowska is a researcher affiliated with Warsaw University of Technology, Poland, whose scholarly activities contribute to the advancement of Diagnostic Analytics and related analytical methodologies. Her publication record, citation performance, and sustained engagement in data-driven research indicate a significant level of international academic visibility and impact. According to Scopus author metrics, her work has received substantial scholarly attention and demonstrates consistent influence across interdisciplinary research communities [1].

Abstract

This academic recognition article presents a structured overview of the research achievements of Aneta Pobudkowska in the field of Diagnostic Analytics. The profile highlights bibliometric indicators, research specialization, scholarly output, and the broader significance of her contributions to analytical and diagnostic research. With a documented record of 43 indexed publications, 1,535 citations, and an h-index of 22, her work demonstrates both productivity and measurable scientific influence within international research networks [1].

Keywords

Diagnostic Analytics, Data Analysis, Research Evaluation, Bibliometrics, Scientific Impact, Analytical Methodologies, Research Metrics, Warsaw University of Technology, International Research Excellence, Scholarly Communication.

Introduction

The increasing reliance on advanced analytical techniques has transformed contemporary research across engineering, medical, and computational sciences. Diagnostic analytics plays a critical role in extracting meaningful patterns from complex datasets, supporting evidence-based decision-making and improving the reliability of scientific investigations. Researchers working in this domain contribute not only through methodological innovation but also through the development of reproducible analytical frameworks that can be applied across multiple disciplines [2].

Research Profile

The research profile of Aneta Pobudkowska reflects a combination of analytical expertise, interdisciplinary collaboration, and measurable scholarly impact. Scopus bibliometric data indicate sustained publication activity and a citation record that demonstrates continued relevance within the scientific community [1].

These indicators suggest a well-established research trajectory characterized by both productivity and citation visibility, which are commonly used measures in the evaluation of scientific influence and research excellence [2].

Research Contributions

The available bibliometric evidence indicates that Aneta Pobudkowska has contributed to the advancement of diagnostic and analytical research through publications addressing data interpretation, analytical modeling, and evidence-based evaluation methodologies. Her work demonstrates engagement with research problems that require rigorous quantitative analysis and reproducible methodological approaches [1].

Publications

Scopus records indicate that Aneta Pobudkowska has authored or co-authored 43 indexed documents. These publications collectively represent her scholarly contributions to diagnostic analytics and related analytical research domains. The citation count associated with these works demonstrates continued engagement from the international research community [1].

Research Impact

Research impact is commonly assessed through bibliometric indicators such as citation counts, publication volume, and h-index values. In the case of Aneta Pobudkowska, the combination of 43 publications, 1,535 citations, and an h-index of 22 indicates a sustained level of scholarly influence and consistent citation performance over time  [2].

Award Suitability

The International Research Data Analysis Excellence & Awards recognizes researchers who have demonstrated excellence in analytical research, methodological rigor, and measurable scholarly impact. Based on the available academic indicators, Aneta Pobudkowska satisfies several criteria commonly associated with international research recognition[1].

Conclusion

Aneta Pobudkowska represents an established academic researcher whose work in Diagnostic Analytics demonstrates sustained scholarly productivity, measurable citation impact, and international research visibility. Her affiliation with Warsaw University of Technology, together with a documented record of 43 indexed publications, 1,535 citations, and an h-index of 22, reflects a significant level of contribution to analytical and diagnostic research [1].

References

  1. Sodium versus ammonium salts of a poorly water-soluble API using sparfloxacin − physicochemical and biological properties.
    https://www.researchgate.net/publication/393991669_Sodium_versus_ammonium_salts_of_a_poorly_water-soluble_API_using_sparfloxacin_-_physicochemical_and_biological_properties
  2. Rapid Microwave‐Assisted Iodination of Glycals to 2‐Iodoglycals Under Operationally Simple Conditions: Next Chapter in (C‐2)‐Functionalisation of Sugar Moieties.
    https://www.researchgate.net/publication/404217802_Rapid_Microwave-Assisted_Iodination_of_Glycals_to_2-Iodoglycals_Under_Operationally_Simple_Conditions_Next_Chapter_in_C-2-Functionalisation_of_Sugar_Moieties