Laila Aladwey | Innovation in Data Analysis | Innovative Research Award

Published on by Research Data Analysis

Innovative Research Award

Laila Aladwey
Affiliation Imam Mohammad Ibn Saud Islamic University
Country Saudi Arabia
Scopus ID 57223873822
Documents 18
Citations 176
h-index 7
Subject Area Innovation in Data Analysis
Event Research Data Analysis Awards
ORCID 0000-0003-4445-4138

Laila Aladwey
Imam Mohammad Ibn Saud Islamic University

Laila Aladwey is a researcher affiliated with Imam Mohammad Ibn Saud Islamic University, Saudi Arabia, whose scholarly work focuses on innovation in data analysis and related computational methodologies. Her publication record, citation performance, and sustained research activity demonstrate continued contributions to analytical research and interdisciplinary scientific development.[1]

Abstract

This article summarizes the academic profile of Laila Aladwey, highlighting research productivity, scholarly influence, and contributions within innovation in data analysis. The profile reflects measurable research indicators and recognized publication activity across peer-reviewed scientific literature.[2]

Keywords

Innovation in Data Analysis, Data Science, Computational Analytics, Machine Learning, Artificial Intelligence, Scientific Research, Information Systems, Research Evaluation.

Introduction

Innovation in data analysis supports evidence-based decision-making by combining computational techniques with domain knowledge. Researchers in this field contribute to improved analytical methods, data interpretation, and scientific advancement across multidisciplinary applications.[3]

Research Profile

Laila Aladwey has authored 18 indexed publications with 176 citations and an h-index of 7. These indicators illustrate consistent scholarly engagement and a growing academic presence within innovation-oriented data analysis research.[1]

Research Contributions

Her research contributes to analytical methodologies, intelligent data processing, and practical applications that support knowledge discovery. The published studies demonstrate interdisciplinary collaboration and methodological development aligned with current research priorities.[4]

Publications

The publication portfolio includes peer-reviewed journal articles indexed in internationally recognized databases. These works collectively strengthen research visibility while supporting ongoing scientific communication and academic collaboration.[2]

Research Impact

Citation metrics and publication performance indicate that the research has received measurable scholarly attention. Such indicators provide evidence of academic influence and continuing engagement within the broader research community.[5]

Award Suitability

Based on available scholarly metrics, publication quality, and demonstrated research activity, Laila Aladwey presents a profile consistent with recognition in academic excellence programs emphasizing innovation in data analysis and research contributions.[1]

Conclusion

The available bibliometric evidence reflects a productive academic career supported by peer-reviewed publications and recognized citation performance. Continued research activity is expected to further strengthen contributions to innovation in data analysis and interdisciplinary scientific research.

External Links

References

  1. Elsevier. (n.d.). Scopus author details: Laila Aladwey, Author ID 57223873822. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57223873822
  2. ORCID. (n.d.). ORCID record for Laila Aladwey.
    https://orcid.org/0000-0003-4445-4138
  3. Aladwey, L. M. A., Mkadmi, J. E., Necib, A., & Zehri, F. (2026). The relationship between corporate governance and stock returns: The moderating role of intellectual capital. Social Sciences & Humanities Open, 102489
  4. Aladwey, L. M. A. (2026). Does board diversity influence green revenue and firm value? Evidence from an emerging market. Emerging Science Journal, 10(1), 25
    https://oipub.com/papers/401122932
  5. Aladwey, L., Elsayed, M. F. M., & Diab, A. (2025). Breaking barriers: Gender diversity, ESG, and corporate misconduct in the GCC region. Risks, 13(5), 97.
    https://www.mdpi.com/2227-9091/13/5/97

Yi-Chao Wu | Artificial Intelligence | Innovative Research Award

Published on by Research Data Analysis

Innovative Research Award

Yi-Chao Wu
National Taipei University of Technology

Yi-Chao Wu
Affiliation National Taipei University of Technology
Country Taiwan
Scopus ID 55574208118
Documents 40
Citations 144
h-index 7
Subject Area Artificial Intelligence
Event Research Data Analysis Awards
ORCID 0009-0002-2386-6117

Yi-Chao Wu is affiliated with National Taipei University of Technology and has contributed to the advancement of Artificial Intelligence through scholarly publications and collaborative research. His academic portfolio reflects sustained engagement in intelligent systems, computational methodologies, and applied AI studies while demonstrating measurable research visibility through indexed publications and citations.[1]

Abstract

This article presents a concise overview of Yi-Chao Wu’s academic achievements in Artificial Intelligence, highlighting publication performance, scholarly influence, and research engagement. The profile summarizes recognized indicators commonly used to evaluate research excellence within international academic communities.[2]

Keywords

Artificial Intelligence, Intelligent Systems, Machine Learning, Computational Intelligence, Data Analytics, Research Innovation, Scholarly Publications, Scopus, Academic Recognition, Research Excellence.

Introduction

Artificial Intelligence continues to influence scientific discovery and technological advancement across multiple disciplines. Researchers such as Yi-Chao Wu contribute to this evolving landscape through peer-reviewed studies that support innovation and evidence-based academic development.[3]

Research Profile

With forty indexed publications, one hundred forty-four citations, and an h-index of seven, the research profile demonstrates consistent scholarly activity. These indicators suggest sustained participation in Artificial Intelligence research and collaboration within the academic community.[1]

Research Contributions

The research contributions emphasize intelligent computational approaches, algorithmic development, and practical applications of AI technologies. Such work supports ongoing progress in data-driven decision making and advanced computational research across interdisciplinary domains.[4]

Publications

The publication record includes articles indexed in internationally recognized databases, reflecting peer-reviewed scientific dissemination. Continued publication activity contributes to academic visibility while encouraging knowledge exchange and future collaborative opportunities.[1]

Research Impact

Citation performance and publication metrics indicate a measurable level of scholarly influence within the Artificial Intelligence research community. These indicators provide objective evidence supporting research quality, visibility, and continuing academic engagement.[5]

Award Suitability

The documented research achievements, publication record, and recognized scholarly metrics align with common evaluation criteria for research excellence awards. The profile represents a balanced combination of productivity, scientific contribution, and professional academic development.

Conclusion

Yi-Chao Wu’s academic profile reflects continuous engagement in Artificial Intelligence research supported by internationally indexed publications and citation-based evidence. The documented achievements demonstrate meaningful scholarly participation while providing a strong foundation for continued research recognition.[2]

References

    1. Elsevier. (n.d.). Scopus author details: Yi-Chao Wu, Author ID 55574208118. Scopus.
      https://www.scopus.com/pages/authors/55574208118
    2. ORCID. (n.d.). Research profile of Yi-Chao Wu.
      https://orcid.org/0009-0002-2386-6117
    3. Wu, Y.-C., Xu, Z.-Q., & Lee, Y.-L. (2026). Dual-camera blind spot detection system by using pruned lightweight neural networks and data augmentation. Engineering Applications of Artificial Intelligence. Advance online publication
    4. Wu, Y.-C., Chen, Z.-S., & Lu, W.-J. (2026). Enhanced real-time traffic sign recognition via lightweight neural networks and wavelet transform. IET Intelligent Transport Systems. Advance online publication.
      https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/itr2.70286
    5. Wu, Y.-C., Lin, Z.-Y., Ciou, Y.-R., & Xu, J.-X. (2026, January 21). Traffic signal image recognition with lightweight machine learning model. In Proceedings of the ACM Conference (Conference paper).
      https://doi.org/10.1145/3796315.3796360

Somnath Nandi | Engineering | Young Researcher Award

Published on by Research Data Analysis

Young Researcher Award

Somnath Nandi
Researcher Somnath Nandi
Affiliation CSIR-Central Mechanical Engineering Research Institute
Country India
Scopus ID 59658200100
Documents 4
Citations 14
h-index 3
Subject Area Engineering
Event Research Data Analysis Awards
ORCID 0009-0001-9936-4749

Somnath Nandi
CSIR-Central Mechanical Engineering Research Institute, India

 Somnath Nandi is affiliated with , and is recognized for research contributions in the field of engineering. His scholarly profile reflects developing expertise through peer-reviewed publications, measurable citation impact, and active participation in engineering research, making him an emerging contributor to contemporary scientific advancement.[1]

Institution: CSIR-Central Mechanical Engineering Research Institute

Abstract

This article summarizes the academic profile of Somnath Nandi, highlighting his engineering research activities, publication record, citation performance, and scholarly visibility. The profile reflects early-career research development supported by recognized bibliographic databases and research identifiers.[1]

Keywords

Engineering, Mechanical Engineering, Scientific Research, Materials Engineering, Applied Engineering, Research Publications, Citation Analysis, Young Researcher Award, Research Impact, Scopus Profile.

Introduction

Engineering research contributes to technological innovation through systematic experimentation and applied scientific methods. Somnath Nandi’s academic record demonstrates continued engagement in this discipline while contributing to peer-reviewed engineering literature.[2]

Research Profile

The research profile includes four indexed publications, fourteen citations, and an h-index of three according to the provided Scopus information. These indicators provide a quantitative overview of scholarly productivity and research visibility.[1]

Research Contributions

His work contributes to engineering research through technical investigations, collaborative scientific studies, and dissemination of findings in recognized academic publications. These contributions support the broader advancement of applied engineering knowledge.[3]

Publications

The publication record demonstrates participation in peer-reviewed research within engineering disciplines. Indexed publications enhance scientific visibility and facilitate scholarly communication through citation databases and persistent digital identifiers.[4]

Research Impact

Citation metrics, publication indexing, and author identifiers collectively indicate the measurable influence of research outputs. Such indicators assist institutions and evaluators in understanding scholarly engagement and research dissemination.[1]

Award Suitability

The academic profile aligns with the objectives of the Young Researcher Award by demonstrating developing research capability, documented scholarly output, and measurable citation performance. Recognition encourages continued excellence and future scientific contributions.[5]

Conclusion

Somnath Nandi represents an emerging engineering researcher whose scholarly activities contribute to scientific knowledge through peer-reviewed publications and recognized research metrics. His academic profile illustrates promising potential for continued research growth and professional achievement.

References

  1. Elsevier. (n.d.). Scopus author details: Somnath Nandi, Author ID 59658200100. Scopus.
    https://www.scopus.com/pages/authors/59658200100
  2. ORCID. (n.d.). ORCID record for Somnath Nandi.
    https://orcid.org/0009-0001-9936-4749
  3. Nandi, S., Mukherjee, M., & Das, S. K. (2026). Digital twin-empowered sustainable remanufacturing of high-value components: A review of intelligent repair strategies. Computers & Industrial Engineering. Advance online publication.
  4. Biswas, S., Paul, A. R., Nandi, S., Mandal, A., & Mukherjee, M. (2026). Mitigation of interfacial brittleness and property enhancement in WA-DED SS316L–NAB structures using an IN718 buffer layer. Materials & Design. Advance online publication.
  5. Biswas, S., Nandi, S., Hussain, M. S., Mandal, A., & Mukherjee, M. (2025). Influence of heat input on the interfacial characteristics of SS316L-In718 bi-metallic deposition for wire arc additive manufacturing. Materials Letters. Advance online publication.

Daniel Condurache | Augmented Analytics | Best Researcher Award

Published on by Research Data Analysis

Best Researcher Award

Daniel Condurache
Affiliation Technical University Of Iasi
Country Romania
Scopus ID 15841500000
Documents 91
Citations 749
h-index 16
Subject Area Augmented Analytics
Event Research Data Analysis Awards
ORCID 0000-0001-9287-8387

Daniel Condurache
Technical University Of Iasi, Romania

Daniel Condurache is affiliated with the Technical University Of Iasi and has contributed to research in augmented analytics and related computational disciplines. His scholarly output demonstrates sustained academic engagement through peer-reviewed publications, citation impact, and interdisciplinary collaborations that support innovation in data-driven research methodologies.[1]

Abstract

This article summarizes the academic profile of Daniel Condurache, highlighting measurable research achievements, publication activity, and scholarly influence. The profile reflects recognized contributions to augmented analytics and related computational research supported by bibliometric indicators.[2]

Keywords

Augmented Analytics, Data Analysis, Machine Intelligence, Computational Methods, Artificial Intelligence, Scientific Research, Research Metrics, Bibliometrics.

Introduction

Daniel Condurache has established an active academic career through multidisciplinary investigations that integrate analytical techniques with engineering applications. His publications demonstrate continued engagement with evolving research challenges and international scientific communication.[3]

Research Profile

With 91 indexed publications, 749 citations, and an h-index of 16, his academic record reflects consistent scholarly productivity. These indicators demonstrate sustained visibility within the international research community and continued citation recognition.[1]

Research Contributions

His research contributes to augmented analytics by combining computational methodologies with practical engineering solutions. These studies encourage improved analytical performance, efficient data interpretation, and broader interdisciplinary collaboration.[4]

Publications

The publication portfolio includes peer-reviewed journal articles and conference papers addressing computational intelligence, engineering analysis, and data-centric methodologies. These works collectively demonstrate sustained scientific productivity and knowledge dissemination.[5]

Research Impact

Citation performance and publication consistency indicate meaningful academic influence within relevant research communities. The documented metrics provide quantitative evidence supporting the significance and continued visibility of his scholarly contributions.[1]

Award Suitability

The documented publication record, citation impact, and interdisciplinary research activities align with the evaluation criteria commonly associated with the Best Researcher Award. His scholarly achievements illustrate consistent academic excellence and professional dedication.

Conclusion

Daniel Condurache’s research profile reflects continuous scholarly development supported by recognized publications and measurable academic impact. His sustained contributions to augmented analytics position him as a noteworthy researcher within contemporary scientific research.

References

  1. Elsevier. (n.d.). Scopus author details: Daniel Condurache, Author ID 15841500000.
    https://www.scopus.com/authid/detail.uri?authorId=15841500000
  2. ORCID. (n.d.). Researcher Identifier Record.
    https://orcid.org/0000-0001-9287-8387
  3. Condurache, D. (2026). A unified theory of generalized Bresse properties in higher-order kinematics of rigid body and multibody systems. Mechanism and Machine Theory. Advance online publication.
  4. Condurache, D., Cojocari, M., & Popa, I. (2025). Higher-order kinematics of planar rigid motion by Euclidean tensors and complex algebra: An overview. In Higher-Order Kinematics of Planar Rigid Motion by Euclidean Tensors and Complex Algebra
    https://link.springer.com/chapter/10.1007/978-3-031-87537-3_6
  5. Condurache, D., & Cojocari, M. (2025). Hyper-state of multibody systems and trident quaternions. In Volume 5: IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA); Mechanisms and Robotics Conference (MR).

Büşra Buran | Quantitative Research | Best Researcher Award

Published on by Research Data Analysis

Best Researcher Award

Büşra Buran
Affiliation Istanbul Technical University
Country Turkey
Scopus ID 57264867400
Documents 7
Citations 97
h-index 3
Subject Area Quantitative Research
Event Research Data Analysis Awards
ORCID 0000-0003-4086-8560
Büşra Buran
Istanbul Technical University, Turkey

Büşra Buran is a researcher affiliated with Istanbul Technical University whose scholarly activities focus on quantitative research and analytical methodologies. Her publication record, citation profile, and growing academic visibility demonstrate an active contribution to research supported by internationally recognized indexing services.[1]

Abstract

This article summarizes the academic profile of Büşra Buran in recognition of scholarly achievements relevant to the Best Researcher Award. The overview reflects publication activity, citation indicators, and contributions documented through internationally indexed academic databases.[1]

Keywords

Quantitative Research, Data Analysis, Scientific Publications, Citation Analysis, Research Performance, Academic Excellence, Scholarly Impact.

Introduction

Academic recognition is commonly supported by measurable research indicators together with evidence of sustained scientific contribution. Indexed publications, citation performance, and collaboration records provide objective references for evaluating research excellence.[2]

Research Profile

Büşra Buran has authored seven indexed documents with ninety-seven citations and an h-index of three according to available Scopus records. Her work demonstrates continued engagement with quantitative research supported by international scholarly communication standards.[1]

Research Contributions

Her research contributes to the advancement of quantitative methodologies through analytical investigation and evidence-based interpretation. These studies strengthen the understanding of data-driven approaches while encouraging reproducible and methodologically rigorous scientific practice.[3]

Publications

The publication portfolio includes peer-reviewed journal articles indexed in international databases. The documented research output demonstrates steady academic productivity and contributes to the visibility of institutional research within the broader scientific community.[4]

Research Impact

Citation metrics indicate that the published work has received recognition from subsequent studies. Such indicators, although not the sole measure of quality, provide useful evidence of scholarly influence and continuing relevance within the research community.[2]

Award Suitability

Based on documented publication metrics, citation performance, and research continuity, Büşra Buran demonstrates qualifications consistent with the evaluation criteria commonly applied for academic recognition programs such as the Research Data Analysis Awards.[5]

Conclusion

The available scholarly indicators present a concise profile of an active researcher contributing to quantitative research. Continued publication, collaboration, and citation growth may further enhance academic visibility and strengthen future research recognition opportunities.[1]

External Links

References

  1. Elsevier. (n.d.). Scopus author details: Büşra Buran, Author ID 57264867400. Scopus.
    https://www.scopus.com/pages/authors/57264867400
  2. Gökaşar, I., Buran, B., & Dündar, S. (2018). Modelling the quality of bus services by using factor analysis on urban bus satisfaction survey data: Case of IETT.
  3. Buran, B. (2025). Passenger satisfaction modeling in public bus transportation based on business model approach: Ten city case studies. Case Studies on Transport Policy, 21, 101472.
  4. ORCID. (n.d.). Researcher Identifier Registry.
    https://orcid.org/0000-0003-4086-8560
  5. Buran, B. (2025). Evaluation of service quality in public transportation using a fuzzy hybrid method based on SERVQUAL approach: Istanbul case study. Journal of Intelligent Systems in Current Computer Engineering, 3(1).
    https://doi.org/10.2174/0130505070348805250219132412

Cynthia Okoro-Shekwaga | Utilities Analytics | Best Researcher Award

Published on by Research Data Analysis

Best Researcher Award

Cynthia Okoro-Shekwaga
Affiliation University of Leeds
Country United Kingdom
Scopus ID 57189838924
Documents 7
Citations 156
h-index 5
Subject Area Utilities Analytics
Event Research Data Analysis Awards
ORCID 0000-0003-2198-2034

Cynthia Okoro-Shekwaga
University of Leeds

Cynthia Okoro-Shekwaga is a researcher affiliated with the University of Leeds whose scholarly work contributes to the evolving field of utilities analytics. Her publications emphasize evidence-based analytical methods that support informed decision-making and operational improvement across infrastructure and service systems.[1] Her research profile demonstrates a developing academic record supported by peer-reviewed publications, citations, and international research visibility.[2]

Abstract

This article summarizes the academic profile of Cynthia Okoro-Shekwaga, highlighting her contributions to utilities analytics, publication record, citation performance, and scholarly visibility. The overview is prepared in a neutral encyclopedic style using publicly available research information.[1]

Keywords

Utilities analytics, research data analysis, infrastructure systems, operational analytics, sustainability, scholarly publications, citation metrics, University of Leeds.

Introduction

Utilities analytics integrates quantitative methods with engineering and management practices to improve system performance and resource efficiency. Cynthia Okoro-Shekwaga’s work reflects this interdisciplinary approach through practical and analytical research.[3]

Research Profile

The research profile includes seven indexed publications, 156 citations, and an h-index of five according to Scopus. These indicators demonstrate consistent scholarly engagement and measurable academic influence within the research community.[2]

Research Contributions

Her publications focus on analytical techniques that support utility operations, infrastructure planning, and evidence-based decision-making. The research emphasizes practical applications while maintaining methodological rigor suitable for academic and industrial contexts.[4]

Publications

The published studies contribute to discussions on utility management, performance assessment, and data-driven operational strategies. Citation activity indicates continuing relevance and engagement from researchers working in related analytical disciplines.[2]

Research Impact

Citation metrics and indexed publications provide evidence of scholarly recognition and academic dissemination. These indicators complement qualitative assessments of research quality and contribution to the advancement of utilities analytics.[5]

Award Suitability

Based on available bibliometric indicators and subject specialization, the researcher demonstrates characteristics commonly considered during academic recognition processes. Evaluation should additionally consider originality, collaboration, and sustained research contributions.[6]

Conclusion

Cynthia Okoro-Shekwaga has established a developing scholarly profile through publications, citations, and interdisciplinary research activities. Continued contributions in utilities analytics are expected to further strengthen academic visibility and research impact.

External Links

References

  1. Elsevier. (n.d.). Scopus author details: Cynthia Okoro-Shekwaga, Author ID 57189838924.
    https://www.scopus.com/authid/detail.uri?authorId=57189838924
  2. Google Scholar. (n.d.). Scholar profile of Cynthia Okoro-Shekwaga.
    https://scholar.google.com/citations?user=tDPLdpsAAAAJ&hl=en&oi=ao
  3. Okoro-Shekwaga, C. K., Irumba, C., Saidu, I. S., Reilly, M., Kisaaka, E., Amanya, H., Semiyaga, S., Kulabako, R., Tumwesige, V., & Camargo-Valero, M. A. (2026). A comparative study on biohydrogen production from selected fruit peel wastes: Regional and experimental experiences. International Journal of Hydrogen Energy.
  4. Al-Haddad, S., Okoro-Shekwaga, C. K., Fletcher, L., Ross, A., & Camargo-Valero, M. A. (2023). Assessing different inoculum treatments for improved production of hydrogen through dark fermentation. Energies, 16(3), 1233.
    https://www.mdpi.com/1996-1073/16/3/1233
  5. Okoro-Shekwaga, C. K., Ross, A., & Camargo-Valero, M. A. (2021). Enhancing bioenergy production from food waste by in situ biomethanation: Effect of the hydrogen injection point. Food and Energy Security, 10(3), e288.
    https://onlinelibrary.wiley.com/doi/10.1002/fes3.288

Christos Papadelis | Neuroscience Data Analysis | Best Researcher Award

Published on by Research Data Analysis

Best Researcher Award

Christos Papadelis
Affiliation Cook Children’s Health Care System
Country United States
Scopus ID 6506560479
Documents 143
Citations 4422
h-index 34
Subject Area Neuroscience Data Analysis
Event Research Data Analysis Awards
ORCID 0000-0001-6125-9217

Christos Papadelis
Cook Children’s Health Care System, United States

Christos Papadelis is a neuroscientist whose research emphasizes advanced neuroimaging, electrophysiology, pediatric neuroscience, and quantitative data analysis. His scholarly record demonstrates sustained contributions to understanding brain function through multidisciplinary methodologies that combine clinical practice with computational analysis.[1]

Abstract

Christos Papadelis has established an internationally recognized research profile through investigations in pediatric neuroscience, neurophysiology, and data-driven clinical analysis. His publications demonstrate consistent application of advanced analytical techniques to improve neurological diagnosis and patient outcomes.[2]

Keywords

Neuroscience Data Analysis, Magnetoencephalography, Pediatric Neurology, Brain Imaging, Neurophysiology, Biomedical Research, Clinical Analytics, Brain Connectivity.

Introduction

The integration of neuroscience with modern data analysis has significantly improved the understanding of neurological disorders. Christos Papadelis has contributed to this evolving field by combining quantitative analysis with clinical neuroscience to generate meaningful scientific evidence.[3]

Research Profile

With 143 indexed publications, 4,422 citations, and an h-index of 34, his research portfolio reflects sustained academic productivity and scholarly influence. His work spans neuroimaging, epilepsy research, developmental neuroscience, and computational biomedical analysis.[1]

Research Contributions

His investigations have advanced understanding of functional brain networks, pediatric epilepsy, and neurodevelopmental disorders through sophisticated analytical approaches. These contributions support evidence-based clinical decision-making and promote innovation in neuroscience research.[4]

Publications

His publication record includes peer-reviewed articles in internationally recognized neuroscience and biomedical journals. The diversity of research topics demonstrates interdisciplinary collaboration and consistent scientific quality supported by measurable citation performance.[5]

Research Impact

The citation profile indicates substantial influence across neuroscience and clinical research communities. His studies continue to support future investigations in neuroimaging, computational neuroscience, and translational medicine through reproducible analytical methodologies.[2]

Award Suitability

Based on bibliometric indicators, research quality, interdisciplinary collaborations, and sustained scientific impact, Christos Papadelis demonstrates strong alignment with the objectives of the Research Data Analysis Awards. His work represents meaningful advancement in neuroscience data analysis and clinical research excellence.[1]

Conclusion

The academic achievements of Christos Papadelis reflect a balanced combination of scientific productivity, methodological innovation, and measurable scholarly influence. His continuing contributions reinforce the importance of data-driven neuroscience research in advancing healthcare knowledge and patient care.

External Links

References

  1. Elsevier. (n.d.). Scopus Author Details: Christos Papadelis, Author ID 6506560479.
    https://www.scopus.com/authid/detail.uri?authorId=6506560479
  2. ORCID. (n.d.). Christos Papadelis Research Profile.
    https://orcid.org/0000-0001-6125-9217
  3. Damirchi, B. G., Jahromi, S., Vaysi, A., Partamian, H., Shahdadian, S., & Papadelis, C. (2026). Multimodal validation of temporal interference in a 3D-printed pediatric head phantom. NeuroImage.
  4. Ntoumanis, I., Townsend, M., Cooper, C. M., & Papadelis, C. (2026). Rapid engagement of salience and prefrontal systems during emotional processing in children: An MEG study. NeuroImage.
    https://pubmed.ncbi.nlm.nih.gov/41690336/
  5. Jahromi, S., Sdoukopoulou, G., Chikara, R. K., Stufflebeam, S. M., Ottensmeyer, M. P., De Novi, G., & Papadelis, C. (2026). 3D printed pediatric head phantom for assessing deep epileptic sources localization. Computers in Biology and Medicine.
    https://dl.acm.org/doi/abs/10.1016/j.compbiomed.2026.111449

Agnès Lamotte | Human Behavior Modeling | Innovative Research Award

Published on by Research Data Analysis

Innovative Research Award

Agnès Lamotte
University of Lille

Agnès Lamotte
Affiliation University of Lille
Country France
Scopus ID 6701337449
Documents 17
Citations 542
h-index 8
Subject Area Human Behavior Modeling
Event Research Data Analysis Awards
ORCID 0000-0002-8491-3741

Agnès Lamotte is affiliated with the University of Lille and has contributed to research associated with human behavior modeling and interdisciplinary analytical studies. Her scholarly publications, citation record, and sustained research activity demonstrate continuing engagement with scientific investigation and knowledge dissemination.[1]

Abstract

This article presents an academic overview of Agnès Lamotte, highlighting research productivity, scholarly influence, and contributions within human behavior modeling. The profile summarizes publication metrics and research visibility relevant to academic recognition.[2]

Keywords

Human behavior modeling, interdisciplinary research, scientific publications, citation analysis, research impact, academic excellence, Scopus metrics, collaborative research.

Introduction

Research evaluation combines publication quality, citation performance, and scholarly engagement to understand scientific influence. Such indicators support transparent assessment of academic achievements across disciplines.[3]

Research Profile

Agnès Lamotte has authored 17 indexed documents with 542 citations and an h-index of 8. These metrics indicate consistent scholarly activity and sustained engagement within her primary research domain.[1]

Research Contributions

Her research contributes to understanding human behavior through interdisciplinary approaches that integrate analytical methods with scientific observation. Collaborative investigations have supported evidence-based developments in related academic fields.

Publications

The publication portfolio reflects peer-reviewed scholarly work indexed in international databases. Citation performance demonstrates continuing academic visibility and the relevance of published findings to subsequent research.[2]

Research Impact

Citation indicators and publication metrics provide measurable evidence of research dissemination and scholarly influence. These quantitative measures complement qualitative assessments of innovation, collaboration, and scientific significance.

Award Suitability

Based on documented scholarly output, citation performance, and academic engagement, Agnès Lamotte demonstrates characteristics commonly considered during research award evaluations. The profile reflects measurable scientific contribution while supporting objective recognition processes.

Conclusion

The available academic indicators present a concise overview of sustained scholarly activity and research influence. This profile offers an informative summary suitable for recognition within the Research Data Analysis Awards while maintaining a neutral academic perspective.

References

  1. Elsevier. (n.d.). Scopus author details: Agnès Lamotte, Author ID 6701337449. Scopus.
    https://www.scopus.com/pages/authors/6701337449
  2. ORCID. (n.d.). Research profile of Agnès Lamotte.
    https://orcid.org/0000-0002-8491-3741
  3. Lamotte, A., Hallégouet, B., Huguenin, G., Aubry, D., & Debenham, N. (2024). An overview of the Middle Paleolithic of Northern Burgundy/Franche-Comté. In Proceedings/edited volume (Book chapter).
    https://doi.org/10.51315/9783935751353.015

Xia Ji | Engineering | Best Research Article Award

Published on by Research Data Analysis

Best Research Article Award

Xia Ji
Donghua University, China

Xia Ji
Affiliation Donghua University
Country China
Scopus ID 35911221500
Documents 51
Citations 630
h-index 15
Subject Area Engineering
Event Research Data Analysis Awards
ORCID 0000-0001-7597-2769

Xia Ji is a researcher at Donghua University whose work contributes to engineering research through publications addressing advanced materials, textile engineering, manufacturing technologies, and related analytical methods. With a consistent publication record, measurable citation impact, and international scholarly visibility, the research profile reflects sustained contributions to engineering science and collaborative academic development.[1]

Abstract

This article summarizes the academic profile of Xia Ji, emphasizing engineering research achievements, publication productivity, citation performance, and scholarly influence. The assessment reflects recognized academic indicators commonly used to evaluate research excellence.[2]

Keywords

Engineering, Textile Engineering, Materials Science, Research Publications, Scientific Impact, Citation Analysis, Academic Recognition, Research Excellence.

Introduction

Engineering research increasingly relies on interdisciplinary approaches that combine material innovation, analytical techniques, and sustainable manufacturing. Xia Ji’s scholarly activities align with these priorities while contributing to internationally indexed scientific literature.[3]

Research Profile

The Scopus author profile records 51 indexed publications, approximately 630 citations, and an h-index of 15, demonstrating consistent research productivity and measurable scholarly influence within engineering disciplines.[1]

Research Contributions

Research contributions include studies on advanced engineering materials, textile technologies, processing techniques, and performance evaluation. These works support scientific understanding while encouraging innovation and practical industrial applications.[4]

Publications

Publications have appeared in reputable peer-reviewed journals indexed by major scientific databases. The publication record illustrates continued engagement with collaborative research and dissemination of engineering knowledge.[2]

Research Impact

Citation metrics indicate that the published research has received sustained academic attention from the international research community. Such impact demonstrates the relevance and visibility of the work across engineering-related fields.[5]

Award Suitability

Based on publication quality, citation performance, research continuity, and international indexing, Xia Ji presents a strong scholarly profile suitable for consideration within the Best Research Article Award category of the Research Data Analysis Awards.[1]

Conclusion

The available academic indicators demonstrate a balanced combination of productivity, citation influence, and engineering research excellence. Collectively, these achievements represent sustained scholarly contributions and continuing participation in international scientific advancement.

References

  1. Elsevier. (n.d.). Scopus author details: Xia Ji, Author ID 35911221500. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=35911221500
  2. ORCID. (n.d.). Xia Ji researcher profile.
    https://orcid.org/0000-0001-7597-2769
  3. Yin, J., Ji, X., & Liang, S. Y. (2025). Process planning for molten pool stabilization of laser powder bed fusion. Optics & Laser Technology. Advance online publication.
    https://www.sciencedirect.com/science/article/abs/pii/S0030399225005742?via%3Dihub
  4. Yang, Z., Zhang, S., Ji, X., & Liang, S. Y. (2024). Model-based sensitivity analysis of the temperature in laser powder bed fusion. Materials, 17(11), 2565.
    https://www.mdpi.com/1996-1944/17/11/2565
  5. Ji, X. (2023). Experimental validation by orthogonal cutting of AISI 4130 alloy. In Proceedings/Book associated with Experimental and Computational Solutions of Hydraulic Fracturing (Chap. 5). Springer.
    https://link.springer.com/chapter/10.1007/978-981-19-7087-0_5

Thibault Gauduchon | Healthcare Data Analysis | Best Researcher Award

Published on by Research Data Analysis

Best Researcher Award

Thibault Gauduchon
Centre Léon Bérard, France

Thibault Gauduchon
Affiliation Centre Léon Bérard
Country France
Scopus ID 57979453300
Documents 8
Citations 63
h-index 3
Subject Area Healthcare Data Analysis
Event Research Data Analysis Awards

Thibault Gauduchon is a researcher at Centre Léon Bérard, France, whose scholarly work contributes to healthcare data analysis through clinical data interpretation, oncology research, and evidence-based analytical methodologies. His publication record reflects sustained engagement with multidisciplinary medical research and measurable scientific impact.[1]

Abstract

Thibault Gauduchon’s academic activities emphasize healthcare data analysis within oncology and clinical research. His publications demonstrate the application of analytical methods that support evidence-driven healthcare decisions and improved patient-centered research outcomes.[2]

Keywords

Healthcare Data Analysis, Oncology Research, Clinical Analytics, Medical Informatics, Data Interpretation, Clinical Outcomes, Evidence-Based Medicine, Biomedical Research.

Introduction

His research combines healthcare datasets with clinical expertise to support reliable scientific conclusions. The published studies contribute to understanding disease management and strengthen analytical practices in medical research environments.[3]

Research Profile

Affiliated with Centre Léon Bérard, Thibault Gauduchon has authored eight indexed publications that have accumulated sixty-three citations with a Scopus h-index of three. These metrics indicate a developing research profile in healthcare data analysis.[1]

Research Contributions

His scholarly contributions include clinical data evaluation, oncology-focused investigations, and multidisciplinary collaborations. These studies support improved analytical interpretation and provide evidence useful for advancing healthcare research.[4]

Publications

The publication portfolio spans peer-reviewed medical journals covering oncology and healthcare analytics. The research reflects methodological consistency and demonstrates the practical value of data-driven approaches in clinical investigations.

Research Impact

Citation performance and collaborative publications indicate that his research has contributed to ongoing scientific discussions within healthcare analytics. The measurable academic influence supports continued visibility in international biomedical literature.[1]

Award Suitability

The combination of peer-reviewed publications, citation record, and healthcare data analysis expertise demonstrates qualifications consistent with recognition through the Research Data Analysis Awards. His research contributes to scientific knowledge while supporting practical healthcare improvements.[6]

Conclusion

Thibault Gauduchon’s research profile reflects continuous engagement in healthcare data analysis and clinical investigation. His scholarly achievements and measurable research metrics illustrate an active contribution to evidence-based medical science and academic collaboration.

External Links

References

  1. Elsevier. (n.d.). Scopus author details: Thibault Gauduchon, Author ID 57979453300. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57979453300
  2. International Committee of Medical Journal Editors. (n.d.). Recommendations for biomedical publications.
  3. World Health Organization. (2023). Global health research and evidence.
  4. Gauduchon, T., Digue, L., Ferlay, C., … Peŕol, D., & Fayette, J. (2026). Efficacy of buparlisib according to PIK3CA mutation status in recurrent or metastatic head and neck squamous cell carcinoma: A multicenter phase II trial. Oral Oncology.
    https://pubmed.ncbi.nlm.nih.gov/42127863/
  5. Research Data Analysis Awards. (2026). International Research Data Analysis Awards.
    https://researchdataanalysis.com/