Joana Baptista | Psychology | Best Researcher Award

Published on by Innovation Technologist

Best Researcher Award

Joana Baptista
Iscte – Instituto Universitário de Lisboa, Portugal

Joana Baptista
Affiliation Iscte – Instituto Universitário de Lisboa
Country Portugal
Scopus ID 36611279300
Documents 61
Citations 458
h-index 12
Subject area Psychology
Event Global Innovation Technologist Awards
ORCID 0000-0002-7581-3909

Joana Baptista is a researcher affiliated with Iscte – Instituto Universitário de Lisboa in Portugal, working in the field of psychology. Her research profile includes publications addressing child development, parental perspectives, infant executive functioning and developmental contexts. The Best Researcher Award profile presented here highlights her reported bibliometric indicators and selected recent publications relevant to developmental psychology and child and family research. [1]

Abstract

This article outlines Joana Baptista’s research profile in psychology, with particular attention to recent work concerning child development, parental concerns and early executive functioning. The supplied bibliometric record lists 61 documents, 458 citations and an h-index of 12. Three publications dated September and October 2026 illustrate research themes relating to developmental environments, family experiences and early cognitive development. These indicators provide a descriptive overview rather than an independent assessment of research quality. [1]

Keywords

Developmental psychology; child development; infant executive functioning; parental concerns; attention-deficit/hyperactivity disorder; maternal sensitivity; research impact; Portugal.

Introduction

Developmental psychology examines the cognitive, emotional and social processes that shape human development. Research in this area can inform understanding of early childhood experiences, family relationships and developmental support. Baptista’s supplied publication list reflects these concerns through studies addressing preschool children, parental observations and infant executive functioning. The publications offer a basis for describing the scope of the research profile without inferring findings beyond the available bibliographic information. [2]

Research Profile

The supplied profile identifies Iscte – Instituto Universitário de Lisboa as Baptista’s institutional affiliation and psychology as her subject area. Her listed research themes connect early developmental outcomes with family and environmental influences. The Scopus author identifier and ORCID provide routes for checking bibliographic records and researcher identity. The numerical indicators in the infobox are reported inputs and should be rechecked against the relevant databases when used for formal evaluation. [1]

Research Contributions

The three supplied publications indicate several connected areas of scholarly interest:

  • Developmental environments and stakeholder perspectives concerning preschool children with ADHD.
  • Parental concerns about child development during and after the COVID-19 pandemic.
  • Potential early predictors of infant executive functioning, including maternal sensitivity and mind-mindedness across different contexts.

Together, these topics concern the relationships between early experience, caregiving and child development. The supplied titles establish the publications’ subjects but do not, by themselves, establish the direction or magnitude of reported findings. [3]

Publications

  1. “Risk and protective factors for healthy development in preschool children with ADHD: a qualitative bioecological study of key stakeholders’ perspectives.” Children and Youth Services Review, October 2026.
  2. “Parental Concerns About Child Development During and After the COVID-19 Pandemic.” Infants & Young Children, September 9, 2026.
  3. “Early predictors of infant executive functioning: Contributions of maternal sensitivity and mind-mindedness across distress and non-distress contexts.” Infant Behavior and Development, September 2026.

Research Impact

The supplied bibliometric figures—458 citations across 61 documents and an h-index of 12—offer quantitative indicators of publication and citation activity. Such measures can help contextualise a research career but vary with database coverage, discipline, publication age and citation practices. A comprehensive impact assessment should also consider methodological rigour, contribution to knowledge, collaboration, reproducibility and the practical relevance of findings. [1]

Award Suitability

The Best Researcher Award profile, associated with the Global Innovation Technologist Awards, presents research activity in psychology through reported bibliometric measures and selected recent publications. These materials can support an initial review of disciplinary relevance and scholarly output. Any award decision should additionally rely on documented eligibility criteria, verified publication records, contribution statements and an independent evaluation process. This article does not represent confirmation of an award decision.

Conclusion

Joana Baptista’s supplied profile reflects research interests in developmental psychology, including early childhood development, parental concerns and infant executive functioning. The three listed publications provide specific examples of these themes, while the reported citation metrics offer a quantitative snapshot of scholarly activity. Database verification and qualitative assessment remain important for drawing reliable conclusions about research contribution and award suitability.

References

  1. Elsevier. (n.d.). Scopus author details: Joana Baptista, Author ID 36611279300. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=36611279300
  2. ORCID. (n.d.). Joana Baptista: Researcher identifier 0000-0002-7581-3909.
    https://orcid.org/0000-0002-7581-3909
  3. Elsevier. (2026). Risk and protective factors for healthy development in preschool children with ADHD: a qualitative bioecological study of key stakeholders’ perspectives. Children and Youth Services Review.
    https://doi.org/10.1016/j.childyouth.2026.109330
  4. Wolters Kluwer. (2026). Parental Concerns About Child Development During and After the COVID-19 Pandemic. Infants & Young Children.
    https://doi.org/10.1097/IYC.0000000000000330
  5. Elsevier. (2026). Early predictors of infant executive functioning: Contributions of maternal sensitivity and mind-mindedness across distress and non-distress contexts. Infant Behavior and Development.
    https://doi.org/10.1016/j.infbeh.2026.102219
  6. Global Innovation Technologist Awards. (n.d.). Official awards website.
    innovationtechnologist.com

Masood Ayoub Kaloo | Chemistry and Materials Science | Best Researcher Award

Published on by Innovation Technologist

Best Researcher Award

Masood Ayoub Kaloo
Government Degree College Doda, India

Masood Ayoub Kaloo
Affiliation Govt Degree College Doda
Country India
Scopus ID 55813860300
Documents 15
Citations 230
h-index 8
Subject area Chemistry and Materials Science
Event Global Innovation Technologist Awards

Masood Ayoub Kaloo is a researcher affiliated with Government Degree College Doda, India, whose reported scholarly profile includes publications in chemistry and materials science. His research record includes a contribution to the 2026 article A reversible colorimetric probe for carbonate ion detection with applications in environmental monitoring and molecular logic, published in Results in Chemistry. His reported bibliometric indicators comprise 15 documents, 230 citations and an h-index of 8. These figures provide a quantitative overview of his indexed research output and citation activity, while individual publications offer additional context for examining his scientific contributions. [1] [2]

Abstract

This article presents a scholarly profile of Masood Ayoub Kaloo, focusing on his reported publication metrics, research interests and contribution to chemical sensing research. His listed 2026 publication examines a reversible colorimetric probe for carbonate-ion detection, with potential applications in environmental monitoring and molecular logic. The work connects chemical recognition with observable optical responses, an approach relevant to analytical chemistry. The profile also considers bibliometric indicators in the context of research evaluation and the Global Innovation Technologist Awards. The information presented is based on the supplied researcher details and publication record; it does not constitute an independent assessment of research quality or a confirmed award decision. [1]

Keywords

Masood Ayoub Kaloo; chemistry; materials science; colorimetric sensors; carbonate-ion detection; environmental monitoring; molecular logic; analytical chemistry; bibliometrics; research recognition.

Introduction

Research in chemistry contributes to the development of analytical methods for identifying chemical species and monitoring environmental conditions. Colorimetric probes are of interest because changes in colour can provide a readily observable indication of a chemical interaction. Carbonate-ion detection is relevant to aqueous chemistry and environmental assessment, although practical applications depend on factors such as selectivity, sensitivity, response time and performance in real samples.

A researcher profile provides a structured means of connecting individual publications with broader disciplinary questions. Publication records and citation indicators can help readers locate scholarly contributions, but should be interpreted alongside article content, methodological rigor and independent validation.

Research Profile

The supplied profile identifies Kaloo with Government Degree College Doda in India and places his research within chemistry and materials science. His Scopus author identifier is 55813860300. The reported record contains 15 documents, 230 citations and an h-index of 8. These indicators describe different dimensions of indexed scholarly activity: document count reflects recorded output, citations measure recorded references by other publications, and the h-index combines publication productivity with citation thresholds. [1] [2]

Research Contributions

The supplied publication title identifies a study of a reversible colorimetric probe designed to detect carbonate ions. The stated applications include environmental monitoring and molecular logic. Reversibility is potentially valuable in sensing systems because it may permit repeated detection cycles, while colorimetric responses can support visual interpretation. Assessment of a particular probe requires examination of the complete article, including its chemical design, calibration, selectivity tests, detection limits and experimental conditions. The title alone does not establish performance in field environments. [3]

Publications

The supplied record identifies the following 2026 publication in Results in Chemistry:

  • A reversible colorimetric probe for carbonate ion detection with applications in environmental monitoring and molecular logic. The author listing includes Bashir Ahmed, Wasseem Akbar, Bhagwat Giri Goswami, Masood Ayoub Kaloo and Pawan Kumar, among other contributors.

A DOI was not included in the supplied information and has therefore not been inferred. The publisher record should be consulted for the definitive article citation and DOI, if assigned.

Research Impact

The reported 230 citations indicate that the indexed publications have received scholarly attention, while an h-index of 8 suggests that eight publications have each received at least eight citations, assuming the supplied metrics were calculated consistently. Citation totals can vary across databases and over time. They are influenced by publication age, field practices, collaboration and database coverage. A balanced evaluation should therefore consider the substance and reproducibility of research alongside quantitative indicators. [1]

Award Suitability

The research profile may be considered in relation to the Best Researcher Award associated with the Global Innovation Technologist Awards. Relevant evaluation criteria could include research originality, methodological quality, publication contributions, documented impact and alignment with chemistry and materials science. The supplied metrics provide a starting point rather than a complete assessment. Eligibility, nomination status and the final award outcome must be confirmed through official event documentation.

Conclusion

Masood Ayoub Kaloo’s supplied scholarly profile documents research activity in chemistry and materials science, including a 2026 publication concerning colorimetric carbonate-ion detection. His reported bibliometric indicators offer a concise view of indexed output and citation activity. Further evaluation should examine the full publication record, article-level evidence and verified researcher identifiers. This profile provides a factual basis for academic recognition while distinguishing supplied metrics from independently verified findings and official award decisions.

References

  1. Elsevier. (n.d.). Scopus author details: Masood Ayoub Kaloo, Author ID 55813860300. Scopus. Bibliometric values in this article are reproduced from the supplied profile information and should be checked against the current database record.
    https://www.scopus.com/authid/detail.uri?authorId=55813860300
  2. Ahmed, B., Akbar, W., Goswami, B. G., et al. (2026). A reversible colorimetric probe for carbonate ion detection with applications in environmental monitoring and molecular logic.
  3. Global Innovation Technologist Awards. (n.d.). Official awards website. Award categories, eligibility and outcomes should be verified using official event information.
    innovationtechnologist.com

Afshin Pashabadi | Chemistry and Materials Science | Innovative Research Award

Published on by Innovation Technologist

Innovative Research Award

Afshin Pashabadi
Razi University, Iran

Afshin Pashabadi
Affiliation Razi University
Country Iran
Scopus ID 36918924000
Documents 38
Citations 642
h-index 16
Subject Area Chemistry and Materials Science
Event Global Innovation Technologist Awards
ORCID 0000-0002-3046-2703

Afshin Pashabadi is a researcher affiliated with Razi University in Iran whose documented publications include work related to chemistry, materials science, proton-transfer mechanisms, oxygen evolution electrocatalysis and biomedical applications. His research profile, as represented by the supplied bibliographic information, provides a basis for examining scholarly output, citation activity and contributions across related scientific topics. This article presents an academic overview in the context of the Innovative Research Award associated with the Global Innovation Technologist Awards.

Abstract

This article reviews the available research profile and selected publications associated with Afshin Pashabadi. The supplied records describe three 2023 journal articles addressing proton relays in oxygen evolution reactions, phototriggered structures in biomedical applications and biomimetic approaches to electrocatalysis. These topics connect materials chemistry with energy conversion and biomedical research. The profile reports 38 documents, 642 citations and an h-index of 16. These metrics provide quantitative context but do not independently establish the originality, practical value or quality of individual contributions. [1]

Keywords

Innovative Research Award; Afshin Pashabadi; Razi University; chemistry; materials science; proton relay; oxygen evolution reaction; electrocatalysis; phototriggered structures; biomedical applications; research impact.

Introduction

Scientific innovation frequently develops through the integration of fundamental chemical principles and applied research challenges. Materials designed to facilitate proton transfer may contribute to improved understanding of catalytic processes, while phototriggered systems offer potential approaches for biomedical applications. Reviewing publications across these areas helps clarify research themes and identify opportunities for further investigation. The supplied publication records provide the principal evidence considered here. [2]

Research Profile

The available profile identifies chemistry and materials science as the principal subject area. Reported bibliometric indicators include 38 documents, 642 citations and an h-index of 16. These figures should be interpreted in relation to the date of retrieval, database coverage, co-authorship and disciplinary citation practices. The affiliation is recorded as Razi University; the institutional spelling should be verified against the official university record before publication.

Research Contributions

The selected works represent three complementary scientific directions:

  • Energy-related catalysis: Investigation of oxygen vacancies and proton hopping in inorganic materials for the oxygen evolution reaction. [3]
  • Biomedical applications: Review of phototriggered structures and their emerging biomedical uses. [4]
  • Biomimetic electrocatalysis: Examination of proton-relay mechanisms in Photosystem II as inspiration for oxygen evolution catalyst design. [5]

Publications

  1. “Oxygen Vacancy-Originated Inorganic Proton Relay for the Oxygen Evolution Reaction: Fast Proton Hopping via La-Doped Praseodymium Carbonate Hydroxide.” Journal of Physical Chemistry C (2023).
  2. “Phototriggered structures: Latest advances in biomedical applications.” Acta Pharmaceutica Sinica B (2023).
  3. “What Can be Learned from Proton Relays in Photosystem II toward Complete Biomimicking of Oxygen Evolution Reaction Electrocatalysis?” ChemElectroChem (2023).

Research Impact

The reported citation count and h-index suggest that the researcher’s publications have received scholarly attention within the indexing database. However, citation totals alone cannot determine whether findings have influenced clinical practice, industrial development or subsequent technologies. Such conclusions require examination of individual citing studies, independent replication and evidence of practical application.

Award Suitability

The Innovative Research Award of the Global Innovation Technologist Awards provides a context for recognizing documented scientific contributions. The supplied profile and publications offer potential evaluation evidence in chemistry and materials science. A comprehensive award assessment should additionally consider originality, methodological rigor, individual contribution, research reproducibility and significance beyond citation metrics. This overview does not independently verify an award decision or confirm that the researcher has received the award.

Conclusion

Afshin Pashabadi’s supplied research records cover proton-transfer mechanisms, oxygen evolution electrocatalysis and phototriggered biomedical structures. Together with the reported bibliometric indicators, these publications provide a starting point for reviewing research activity in chemistry and materials science. Further assessment using verified author records and full-text studies would help establish the scope and significance of the contributions.

References

  1. Elsevier. (n.d.). Scopus author details: Afshin Pashabadi, Author ID 36918924000. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=36918924000
  2. ORCID. (n.d.). Afshin Pashabadi researcher identifier.
    https://orcid.org/0000-0002-3046-2703
  3. American Chemical Society. (2023). Oxygen Vacancy-Originated Inorganic Proton Relay for the Oxygen Evolution Reaction: Fast Proton Hopping via La-Doped Praseodymium Carbonate Hydroxide. Journal of Physical Chemistry C. DOI: 10.1021/acs.jpcc.3c06059.
    https://doi.org/10.1021/acs.jpcc.3c06059
  4. Elsevier. (2023). Phototriggered structures: Latest advances in biomedical applications. Acta Pharmaceutica Sinica B. DOI: 10.1016/j.apsb.2023.04.005.
    https://doi.org/10.1016/j.apsb.2023.04.005
  5. Wiley. (2023). What Can be Learned from Proton Relays in Photosystem II toward Complete Biomimicking of Oxygen Evolution Reaction Electrocatalysis? ChemElectroChem. DOI: 10.1002/celc.202300423.
    https://doi.org/10.1002/celc.202300423
  6. Global Innovation Technologist Awards. (n.d.). Official awards website.
    innovationtechnologist.com

Yichao Zhou | Computer Science and Artificial Intelligence | Best Researcher Award

Published on by Innovation Technologist

Best Researcher Award

Yichao Zhou
Nanjing University of Science and Technology, China

Yichao Zhou
Affiliation Nanjing University of Science and Technology
Country China
Scopus ID 56258805600
Documents 29
Citations 261
h-index 10
Subject Area Computer Science and Artificial Intelligence
Event Global Innovation Technologist Awards
Google Scholar ID eMHcFZoAAAAJ

Yichao Zhou is a researcher affiliated with Nanjing University of Science and Technology, China, whose listed scholarly work includes computer vision, three-dimensional face reconstruction, and artificial intelligence applications. The Best Researcher Award profile recognizes the research record presented for consideration at the Global Innovation Technologist Awards. The available bibliographic information highlights contributions to emerging computational methods, including research addressing facial reconstruction and visual media analysis. [1] [2]

Abstract

This academic recognition profile summarizes Yichao Zhou’s reported research metrics and two supplied publication records. The publications concern multiscale transformer-based deepfake detection and weakly supervised multi-view three-dimensional face reconstruction. These topics connect artificial intelligence with image analysis, computer vision, and digital media understanding. The supplied bibliometric figures are 29 documents, 261 citations, and an h-index of 10. These indicators provide a quantitative overview but should be interpreted alongside publication quality, research originality, reproducibility, and practical relevance. [1] [2]

Keywords

Yichao Zhou; computer vision; artificial intelligence; deepfake detection; face reconstruction; transformer networks; multi-view learning; research impact; Best Researcher Award.

Introduction

Artificial intelligence research increasingly supports the analysis and interpretation of visual information. Deepfake detection investigates methods for identifying manipulated media, while three-dimensional face reconstruction seeks to recover facial structure from multiple visual perspectives. Both areas present technical challenges involving feature representation, incomplete information, generalization, and reliable evaluation. Zhou’s supplied publication records place his work within this broader research landscape. [1] [2]

Research Profile

Zhou is associated with Nanjing University of Science and Technology. The supplied records identify research involving visual computing and machine-learning techniques. His listed bibliometric profile reports 29 documents, 261 citations, and an h-index of 10. These figures offer a snapshot of recorded scholarly output and citation activity; they may change as databases are updated. The available information does not establish a complete account of his research appointments, projects, or responsibilities, so this profile focuses on the documented research themes.

Research Contributions

The supplied records indicate two relevant directions:

  • Deepfake detection: Multiscale spatial frequency-aware transformer methods and saturation analysis address the challenge of detecting manipulated visual content. [1]
  • Three-dimensional face reconstruction: Weakly supervised multi-view reconstruction explores approaches to recovering facial geometry and detail from multiple views. [2]

Together, these topics illustrate the relevance of representation learning and visual analysis to contemporary computer science.

Publications

  1. “Multiscale Spatial Frequency-Aware Transformer and Saturation Analysis for Universal Deepfake Detection.” IEEE Transactions on Cybernetics, 2026. The supplied record lists Xu, Hu, Chen, and additional authors, including Hadeel Alsolai and Shahid Mumtaz. [1]
  2. “Weakly Supervised Multi-view 3D Face Reconstruction with More Details.” Proceedings of SPIE – The International Society for Optical Engineering, 2026. The supplied record lists Ao Zhang, Yichao Zhou, Xiyuan Hu, and Xiangyu Li. [2]

DOIs were not included in the supplied publication details and have therefore not been inferred.

Research Impact

The reported 261 citations and h-index of 10 suggest that Zhou’s indexed research has received scholarly attention. Citation indicators alone cannot establish research quality or societal benefit; assessment also requires consideration of methodological rigor, originality, field-specific citation patterns, and independent validation. The supplied records provide an initial basis for reviewing research activity rather than a complete evaluation of impact. [3]

Award Suitability

The documented research topics and reported bibliometric indicators provide relevant material for consideration under the Best Researcher Award at the Global Innovation Technologist Awards. A comprehensive decision should additionally examine original contributions, publication verification, author roles, methodological quality, and relevance to the award criteria. This profile describes the available evidence and does not independently confirm an award decision.

Conclusion

Yichao Zhou’s supplied research records span deepfake detection and multi-view three-dimensional face reconstruction, two areas of continuing interest in artificial intelligence and computer vision. His reported publication and citation indicators provide context for academic recognition. Further assessment against verified bibliographic records and award-specific criteria would support a balanced evaluation of his research contributions.

References

  1. Xu, K., Hu, X., Chen, C., et al. (2026). Multiscale Spatial Frequency-Aware Transformer and Saturation Analysis for Universal Deepfake Detection. IEEE Transactions on Cybernetics.
  2. Zhang, A., Zhou, Y., Hu, X., & Li, X. (2026). Weakly Supervised Multi-view 3D Face Reconstruction with More Details. Proceedings of SPIE – The International Society for Optical Engineering.
  3. Elsevier. (n.d.). Scopus author details: Yichao Zhou, Author ID 56258805600. Scopus. https://www.scopus.com/authid/detail.uri?authorId=56258805600
  4. ORCID. (n.d.). ORCID researcher identifier service.
  5. Global Innovation Technologist Awards. (n.d.). Official awards website.
    innovationtechnologist.com

Ying Tan | Computer Science | Distinguished Scientist Award

Published on by Innovation Technologist

Distinguished Scientist Award

Ying Tan
Peking University, China

                      Ying Tan
Affiliation Peking University
Country China
Scopus ID 56098810800
Documents 359
Citations 8,578
h-index 46
Subject Area Computer Science
Event Global Innovation Technologist Awards
ORCID 0000-0001-8243-4731

The Distinguished Scientist Award profile recognizes Ying Tan’s reported scholarly record in computer science and its relevance to computational intelligence, optimization, and machine learning. Associated publication information includes research on fireworks algorithms, neural network optimization, and time-series prediction. The profile presents bibliometric indicators alongside selected publications to support an informed assessment of research activity. Award recognition remains subject to the event’s applicable evaluation and verification procedures.

Abstract

This article summarizes the supplied research profile of Ying Tan, affiliated with Peking University, China. The reported Scopus metrics comprise 359 documents, 8,578 citations, and an h-index of 46. Selected publications address optimization algorithms, neural networks, and sequence-based prediction. These topics connect computational methods with challenges in efficient model training and data-driven forecasting. The profile provides a structured basis for reviewing publication activity and research visibility, while acknowledging that bibliometric indicators alone cannot establish the originality or practical value of individual contributions. [1]

Keywords

Computer science; computational intelligence; swarm intelligence; fireworks algorithm; neural network optimization; contrastive learning; time-series prediction; bibliometrics; research evaluation.

Introduction

Computer science research increasingly combines optimization strategies, machine learning architectures, and intelligent computational systems. Research evaluation in this environment benefits from considering both measurable scholarly activity and the substance of published work. Ying Tan’s supplied profile and publication records provide examples of research addressing algorithmic search and predictive modeling. The Distinguished Scientist Award context offers an opportunity to assess this work through transparent criteria rather than relying exclusively on citation totals. [2]

Research Profile

The supplied profile identifies Peking University as the institutional affiliation and computer science as the subject area. Reported bibliometric indicators are 359 documents, 8,578 citations, and an h-index of 46. These figures describe the provided record and should be checked against the live Scopus profile before formal publication, since indexing and citation counts can change over time. [1]

Research Contributions

The supplied publication titles indicate several related research directions:

  • Developing fireworks-based optimization methods and investigating their enhancement through multimodal large language models.
  • Exploring contrastive learning to improve selectivity in Mamba-based time-series prediction.
  • Implementing multi-guiding spark fireworks algorithms on GPUs for black-box neural network optimization.

Together, these topics concern search efficiency, predictive modeling, and computational implementation. Their specific contributions should be assessed from the full papers and experimental results. [3]

Publications

  1. “Visual-Enhanced Fireworks Algorithm via multimodal large language models.” Swarm and Evolutionary Computation, listed publication date November 2026. [3]
  2. “Repetitive contrastive learning enhances Mamba’s selectivity in time series prediction.” Neural Networks, April 2026. [4]
  3. “A GPU Implementation of Multi-guiding Spark Fireworks Algorithm for Efficient Black-Box Neural Network Optimization.” Book chapter, 2026.. [5]

The first item’s supplied publication date is November 2026, which is later than the current date of 27 October 2026; it should therefore be treated as forthcoming or scheduled unless the publisher confirms otherwise.

Research Impact

The reported citation count and h-index suggest an established indexed publication record. However, citation indicators vary by discipline, publication age, co-authorship, and database coverage. A balanced assessment should also examine methodological soundness, reproducibility, independent uptake, and the significance of individual findings. DOI records provide stable routes for verifying publication metadata and locating the associated works. [6]

Award Suitability

The profile presents evidence relevant to consideration for a Distinguished Scientist Award, including sustained publication activity, citation visibility, and research spanning optimization and machine learning. A complete award assessment should independently verify affiliation, authorship, publication status, and bibliometric data, and evaluate originality and research quality against the award’s published criteria. This profile does not itself establish an award decision.

Conclusion

Ying Tan’s supplied research profile combines substantial reported bibliometric indicators with publications addressing computational optimization and predictive learning. These details provide a useful starting point for scholarly recognition, provided that publication records and metrics are verified and qualitative research assessment remains central.

References

  1. Elsevier. (n.d.). Scopus author details: Ying Tan, Author ID 56098810800. Scopus. Profile metrics are reported from the supplied input and require current verification.
    https://www.scopus.com/authid/detail.uri?authorId=56098810800
  2. ORCID. (n.d.). Ying Tan researcher identifier. ORCID record.
    https://orcid.org/0000-0001-8243-4731
  3. Elsevier. (2026). Visual-Enhanced Fireworks Algorithm via multimodal large language models. Swarm and Evolutionary Computation. DOI: 10.1016/j.swevo.2026.102577.
    https://doi.org/10.1016/j.swevo.2026.102577
  4. Elsevier. (2026). Repetitive contrastive learning enhances Mamba’s selectivity in time series prediction. Neural Networks. DOI: 10.1016/j.neunet.2025.108290.
    https://doi.org/10.1016/j.neunet.2025.108290
  5. Springer Nature. (2026). A GPU Implementation of Multi-guiding Spark Fireworks Algorithm for Efficient Black-Box Neural Network Optimization. Book chapter. DOI: 10.1007/978-981-95-0982-9_5.
    https://doi.org/10.1007/978-981-95-0982-9_5
  6. Global Innovation Technologist Awards. (n.d.). Official awards website. Award information and applicable recognition criteria should be consulted directly.
    innovationtechnologist.com

Marzieh Shirazi | Nanotechnology | Best Researcher Award

Published on by Innovation Technologist

Best Researcher Award

Marzieh Shirazi
Khatam University, Iran

Marzieh Shirazi
Affiliation Khatam University
Country Iran
Scopus ID 55310909600
Documents 25
Citations 386
h-index 13
Subject Area Nanotechnology
Event Global Innovation Technologist Awards
ORCID 0000-0003-3868-2599

Marzieh Shirazi is a researcher affiliated with Khatam University in Iran whose documented publications address nanotechnology and materials-related research. The available bibliographic information includes studies of aluminium-doped zinc oxide (AZO) surface topography and perovskite solar-cell fabrication. Her reported research metrics provide a quantitative overview of publication and citation activity. This article summarizes the supplied profile information and selected publications in the context of the Best Researcher Award associated with the Global Innovation Technologist Awards. The metrics and publication details should be interpreted in relation to their source and date of retrieval. [1]

Abstract

This article presents a concise overview of Marzieh Shirazi’s research profile and two publications concerning nanostructured AZO surfaces and perovskite solar cells. The supplied profile reports 25 documents, 386 citations and an h-index of 13. These indicators offer complementary perspectives on scholarly output and citation activity but do not independently establish research quality. The selected publications illustrate work involving surface characterization and photovoltaic materials. The profile is presented as contextual information relevant to consideration for the Best Researcher Award; it does not constitute confirmation of an award decision. [1]

Keywords

Marzieh Shirazi; nanotechnology; aluminium-doped zinc oxide; AZO surfaces; perovskite solar cells; photovoltaic materials; surface topography; research impact; scholarly publications; Best Researcher Award.

Introduction

Nanotechnology research investigates materials and structures at small scales to understand their properties and potential applications. Within this field, transparent conducting oxides and photovoltaic materials are relevant to electronic and renewable-energy technologies. Research examining surface morphology, material composition and device construction can help characterize material performance and inform further investigation. Shirazi’s two supplied publications connect these topics through AZO surface analysis and the fabrication of perovskite solar cells. [2] [3]

Research Profile

The supplied profile associates Shirazi with Khatam University, Iran, and identifies nanotechnology as the subject area. Its reported indicators comprise 25 documents, 386 citations and an h-index of 13. A citation count measures recorded citations, while the h-index combines publication productivity and citation frequency under a defined threshold. Values can vary across databases and retrieval dates; therefore, they should be checked against the current Scopus author record before formal publication or evaluation. [1]

Research Contributions

The selected works represent two related areas of materials research:

  • Surface characterization: Contour-loop analysis of multi-affine AZO rough surfaces addresses the description of surface topography, a relevant consideration in thin-film materials research. [2]
  • Photovoltaic materials: Research on hole-conductor-free perovskite solar cells examines an approach based on aluminium-doped zinc oxide and a low-cost carbon electrode. The subject connects materials selection with solar-cell fabrication. [3]

Together, these topics demonstrate a research focus spanning material-surface analysis and photovoltaic device development, without implying outcomes beyond those documented in the publication records.

Publications

  1. “Contour loop analysis of multi-affine nanostructure AZO rough surfaces.” (2019). Surface Topography: Metrology and Properties. [2]
  2. “Fabrication of hole-conductor-free perovskite solar cells based on Al doped ZnO and low-cost carbon electrode.” (2018). Journal of Materials Science: Materials in Electronics. [3]

Research Impact

The reported 386 citations indicate that the indexed publications associated with this profile have received scholarly attention, while an h-index of 13 reflects a combination of publication count and citation distribution. These figures should be assessed alongside methodological rigor, originality, reproducibility, collaboration and relevance to the field. Citation indicators alone cannot establish societal impact or the significance of an individual contribution. [4]

Award Suitability

The supplied profile and publications provide information that may support an assessment for the Best Researcher Award under the Global Innovation Technologist Awards. A balanced review would consider verified bibliographic records, the candidate’s specific contribution to each work, research quality, field context and broader relevance. The profile statistics are descriptive evidence rather than proof of eligibility or selection. Any final recognition should follow the event’s published criteria and verification process.

Conclusion

Marzieh Shirazi’s supplied research profile identifies activity in nanotechnology, with selected publications addressing AZO surface topography and perovskite solar-cell fabrication. The reported publication and citation indicators offer a starting point for scholarly assessment. Verification of the author record, publication metadata and individual research contributions remains important for an accurate and transparent award evaluation.

References

  1. Elsevier. (n.d.). Scopus author details: Marzieh Shirazi, Author ID 55310909600. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=55310909600
  2. “Contour loop analysis of multi-affine nanostructure AZO rough surfaces.” (2019). Surface Topography: Metrology and Properties.
    DOI: https://doi.org/10.1088/2051-672X/ab326f
  3. “Fabrication of hole-conductor-free perovskite solar cells based on Al doped ZnO and low-cost carbon electrode.” (2018). Journal of Materials Science: Materials in Electronics.
    DOI: https://doi.org/10.1007/s10854-018-9054-8
  4. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences, 102(46), 16569–16572.
    DOI: https://doi.org/10.1073/pnas.0507655102
  5. ORCID. (n.d.). Marzieh Shirazi researcher identifier. ORCID.
    https://orcid.org/0000-0003-3868-2599

Rubén Lostado Lorza | Engineering | Best Academic Researcher Award

Published on by Innovation Technologist

Best Academic Researcher Award

Rubén Lostado Lorza
University of La Rioja, Spain

               Researcher profile
Affiliation University of La Rioja
Country Spain
Scopus ID 34872962800
Documents 78
Citations 1,173
h-index 21
Subject Area Engineering
Event Global Innovation Technologist Awards
ORCID 0000-0001-5902-6078

The Best Academic Researcher Award profile recognizes the research record of Rubén Lostado Lorza, an engineering researcher affiliated with the University of La Rioja in Spain. The supplied bibliometric indicators report 78 documents, 1,173 citations, and an h-index of 21. His listed publications address computational modelling, optimization, welding processes, and biomedical engineering applications. These topics illustrate connections between numerical methods, engineering design, and the investigation of complex physical systems. The profile presents available researcher information and selected publications for academic recognition through the Global Innovation Technologist Awards. [1]

Abstract

This article summarizes the academic profile, selected research themes, and reported bibliometric indicators of Rubén Lostado Lorza. The supplied publication information highlights finite element modelling, genetic-algorithm-based optimization, response surface methodology, experimental comparison, and thermal efficiency in welding. Such approaches are relevant to engineering research because they help investigate system behaviour, compare predictive methods, and support evidence-informed design decisions. The article distinguishes reported profile metrics from interpretations of research significance and links readers to available researcher and publication records. [2]

Keywords

Engineering research; finite element modelling; computational optimization; genetic algorithms; response surface methodology; welding processes; biomedical engineering; research impact; academic recognition.

Introduction

Engineering research combines theoretical analysis, computational simulation, and experimental evidence to understand and improve technical systems. Numerical modelling can help researchers examine conditions that are difficult to isolate experimentally, while optimization techniques can identify parameter combinations that improve agreement with observed behaviour. The listed works associated with this profile span manufacturing processes and biomedical modelling, demonstrating the relevance of computational methods across different engineering contexts. Publication records and persistent researcher identifiers provide pathways for readers to verify bibliographic details. [3]

Research Profile

The supplied profile identifies the University of La Rioja as the researcher’s institutional affiliation and Engineering as the subject area. Reported indicators include 78 documents, 1,173 citations, and an h-index of 21. These figures offer a quantitative snapshot, but they may change as databases are updated and depend on indexing coverage, author matching, and citation-counting practices. The Scopus author record and ORCID profile are therefore useful reference points for checking current information. [1]

Research Contributions

The provided publications indicate two notable methodological areas:

  • Computational and biomedical modelling: The listed lumbar intervertebral disc study combines machine learning-based genetic algorithm optimization with finite element models, comparing its approach with response surface methodology and experimental data.
  • Manufacturing and thermal analysis: The welding study investigates how shielded metal arc welding parameters affect thermal efficiency using the finite element method.

Together, these subjects illustrate how simulation and optimization can be applied to different engineering problems. Detailed conclusions about performance or practical benefits require examination of the complete articles and their reported validation results. [4]

Publications

  1. “Machine learning-based GA optimization of lumbar intervertebral disc FE models: Comparison with RSM and experimental data.” Journal of the Mechanical Behavior of Biomedical Materials, listed publication date November 2026. [4]
  2. “A comprehensive investigation of the effects of welding parameters on thermal efficiency in SMAW processes using FEM.” Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, December 12, 2025. [5]

Research Impact

The supplied total of 1,173 citations and h-index of 21 indicates that the indexed publication record has received scholarly attention. Citation counts alone, however, cannot establish research quality, originality, reproducibility, or practical influence. A balanced assessment considers methodological rigour, publication context, independent validation, and the relevance of findings to subsequent research. The figures presented here should be understood as reported profile data rather than an independent bibliometric audit. [1]

Award Suitability

The profile provides relevant material for consideration under the Best Academic Researcher Award at the Global Innovation Technologist Awards. Its reported bibliometric indicators and selected engineering publications offer starting points for reviewing scholarly activity. A formal award decision should additionally consider verified authorship, contribution statements, research quality, and the award’s published eligibility and evaluation criteria. This article does not imply that an award has been conferred.

Conclusion

Rubén Lostado Lorza’s supplied research profile combines substantial reported citation activity with publications concerning computational optimization, biomedical finite element modelling, and welding-process analysis. These areas demonstrate the broad applicability of numerical and data-driven methods in engineering. Verification through the linked author identifiers and original publications remains important for maintaining an accurate and transparent academic recognition profile.

References

  1. Elsevier. (n.d.). Scopus author details: Rubén Lostado Lorza, Author ID 34872962800. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=34872962800
  2. ORCID. (n.d.). Rubén Lostado Lorza: ORCID researcher identifier.
    https://orcid.org/0000-0001-5902-6078
  3. “Machine learning-based GA optimization of lumbar intervertebral disc FE models: Comparison with RSM and experimental data.” (2026). Journal of the Mechanical Behavior of Biomedical Materials. DOI: 10.1016/j.jmbbm.2026.107602.
    https://doi.org/10.1016/j.jmbbm.2026.107602
  4. “A comprehensive investigation of the effects of welding parameters on thermal efficiency in SMAW processes using FEM.” (2025). Energy Sources, Part A: Recovery, Utilization, and Environmental Effects.
    https://doi.org/10.1080/15567036.2025.2520434
  5. Global Innovation Technologist Awards. (n.d.). Official award website.
    innovationtechnologist.com

Mercedes Cao Vilariño | Medicine and Health Sciences | Research Excellence Award

Published on by Innovation Technologist

Research Excellence Award

Mercedes Cao Vilariño
Universitary Hospital, Spain

Mercedes Cao Vilariño
Affiliation Universitary Hospital
Country Spain
Scopus ID 57195055799
Documents 5
Citations 15
h-index 3
Subject Area Medicine and Health Sciences
Event Global Innovation Technologist Awards

Mercedes Cao Vilariño is a researcher associated with medical and health sciences in Spain. Her documented research includes a 2020 publication examining smoking cessation support and carbon monoxide monitoring among kidney transplant patients who smoke. This article presents a research profile and recognition overview for the Research Excellence Award associated with the Global Innovation Technologist Awards. The available bibliographic information and supplied research metrics provide the basis for this summary; further verification is needed to establish a comprehensive publication record and award decision.

Abstract

This profile summarizes the supplied academic indicators and a reported clinical research publication associated with Mercedes Cao Vilariño. The study concerns a randomized clinical trial investigating carbon monoxide monitoring using CO-oximetry and brief anti-smoking advice for kidney transplant recipients who smoke. The topic connects preventive healthcare, tobacco cessation, and the management of health risks in transplant populations. Supplied bibliometric figures list five documents, 15 citations, and an h-index of three; these values should be interpreted according to the source and date of retrieval. [1] [2]

Keywords

Mercedes Cao Vilariño; medicine and health sciences; kidney transplantation; smoking cessation; CO-oximetry; clinical research; preventive medicine; research impact; research excellence.

Introduction

Research excellence in healthcare involves the systematic investigation of clinical questions, evaluation of evidence, and potential translation of findings into practice. Smoking cessation is particularly relevant to patients with complex medical histories, including kidney transplant recipients. Research into brief interventions and objective monitoring methods may inform approaches to identifying tobacco use and supporting cessation. The listed publication provides a specific bibliographic point of reference for understanding this research area. [1]

Research Profile

The supplied profile associates the researcher with a hospital institution in Spain and the subject area of medicine and health sciences. The Scopus author identifier provides a route to reviewing indexed publications and associated citation records. Affiliation details, author-name variants, and profile metrics may change over time; institutional and database records should therefore be consulted for current verification. [2]

Research Contributions

The identified clinical trial addresses two components of smoking-related care: carbon monoxide assessment and brief anti-smoking advice. Its focus on kidney transplant recipients places the investigation within a specialized clinical population. The study title indicates a randomized trial design, although detailed conclusions, sample characteristics, and outcome estimates should be drawn from the full publication rather than inferred from bibliographic metadata alone. [1]

Publications

The supplied record identifies the following publication:

  • “Randomized clinical trial to determine the effectiveness of CO-oximetry and anti-smoking brief advice in a cohort of kidney transplant patients who smoke.” International Journal of Medical Sciences, 2020. The supplied record lists Mercedes Cao Vilariño among the authors. [1]

Research Impact

The supplied indicators report five documents, 15 citations, and an h-index of three. Citation counts offer one measure of scholarly visibility, but they do not independently establish research quality, clinical effectiveness, or societal benefit. A fuller assessment would consider study design, methodological rigor, reproducibility, collaboration, and relevance to patient care. These indicators should be checked against the current Scopus record before formal publication. [2]

Award Suitability

The Research Excellence Award profile highlights a documented contribution to clinical research relevant to tobacco cessation and transplant care. Consideration for recognition may include verified publications, methodological contributions, independent evidence of impact, and the candidate’s wider research record. This profile describes award-related recognition context and does not, by itself, confirm that an award has been formally conferred.

Conclusion

Mercedes Cao Vilariño’s supplied research profile includes a clinical publication on smoking-related intervention in kidney transplant patients. The reported bibliometric indicators offer a concise snapshot of scholarly activity, while a complete evaluation requires examination of the publication, current author records, and broader evidence of research contribution. Accurate attribution and transparent verification remain essential to responsible academic recognition.

References

  1. Seijo-Bestilleiro, R., Seoane-Pillado, M. T., Pértega-Díaz, S. D., Cao Vilariño, M., Gil-Guillén, V. F., et al. (2020). Randomized clinical trial to determine the effectiveness of CO-oximetry and anti-smoking brief advice in a cohort of kidney transplant patients who smoke.
  2. Elsevier. (n.d.). Scopus author details: Mercedes Cao Vilariño, Author ID 57195055799. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57195055799
  3. International Journal of Medical Sciences. (2020). Journal publication record for the randomized clinical trial on CO-oximetry and smoking cessation advice in kidney transplant patients.
  4. Global Innovation Technologist Awards. (n.d.). Official awards website.
    innovationtechnologist.com/

Soyeon Park | Decision Sciences | Best Researcher Award

Published on by Innovation Technologist

Best Researcher Award

Soyeon Park
Lotte Group Research and Development Center, South Korea

Soyeon Park
Affiliation Lotte Group Research and Development Center
Country South Korea
Scopus ID 57213917853
Documents 10
Citations 133
h-index 7
Subject Area Decision Sciences
Event Global Innovation Technologist Awards

Soyeon Park is a researcher affiliated with the Lotte Group Research and Development Center in South Korea. Her reported scholarly profile includes 10 documents, 133 citations, and an h-index of 7. Her research record includes a 2026 publication examining the post-occupancy performance of relocatable modular construction for temporary educational facilities. This work addresses the evaluation of adaptable building methods in educational settings and provides a basis for considering their practical performance after occupation. The profile is presented in connection with the Best Researcher Award category of the Global Innovation Technologist Awards. Bibliographic and citation information should be interpreted in the context of the relevant database records and their update dates. [1] [2]

Abstract

This article presents a concise overview of Soyeon Park’s reported research profile and its relevance to innovation-focused recognition. A highlighted 2026 publication, co-authored with Truong Dang Hoang Nhat Nguyen, Jinhak Jeong, and Yonghan Ahn, investigates post-occupancy evaluation of relocatable modular construction for temporary educational facilities. The topic connects building adaptability, educational infrastructure, and the assessment of facilities in use. Reported bibliometric indicators offer additional context for understanding the visibility of the researcher’s scholarly output. [2]

Keywords

Soyeon Park; Decision Sciences; modular construction; post-occupancy evaluation; temporary educational facilities; research impact; scholarly publications; Best Researcher Award; South Korea; innovation.

Introduction

Researcher recognition commonly considers publication activity, citation indicators, subject relevance, and the contribution of individual studies. Park’s reported profile combines bibliometric measures with research on modular construction and the performance of temporary educational facilities. Such facilities raise questions about flexibility, usability, and the suitability of building solutions for changing institutional needs. Evaluating occupied facilities can help identify practical considerations that may not be fully apparent during design or construction. [2]

Research Profile

The supplied profile records 10 documents, 133 citations, and an h-index of 7. These indicators describe different aspects of indexed research output and citation activity. They should not be treated as independent proof of research quality, and their interpretation depends on database coverage, author attribution, and the date of retrieval. The stated subject area is Decision Sciences, while the highlighted publication concerns construction and architectural management.

Research Contributions

The identified study addresses post-occupancy evaluation of relocatable modular construction for temporary educational facilities. Post-occupancy evaluation examines how a building performs after users begin occupying it. In modular educational settings, this approach can inform discussions of adaptability, operational suitability, and the relationship between facility design and everyday use. The article title establishes the study’s focus, but specific findings and methods should be confirmed from the full publication rather than inferred from bibliographic information alone. [2]

Publications

The supplied publication record identifies the following article:

  • Nguyen, T. D. H. N., Park, S., Jeong, J., & Ahn, Y. (2026). “Post occupancy evaluation of the relocatable modular construction method for temporary educational facilities.” Engineering, Construction and Architectural Management. The DOI and full bibliographic details require verification against the publisher’s record. [2]

Research Impact

The reported 133 citations indicate that the indexed publications have received scholarly attention. An h-index of 7 represents a citation-based measure of publication performance, subject to the database’s coverage and attribution. Neither measure alone establishes the practical or societal impact of a particular study. A fuller assessment would consider the article’s verified findings, subsequent research use, and relevance to decisions about educational infrastructure.

Award Suitability

The Best Researcher Award category of the Global Innovation Technologist Awards provides a context for presenting research activity and potential contributions. Park’s supplied bibliometric indicators and the identified 2026 co-authored publication may be considered as elements of a broader evaluation. A fair award assessment should also review verified authorship, research originality, methodological rigor, publication quality, and relevance to the stated criteria. This profile does not independently establish an award decision or confirmed recipient status.

Conclusion

Soyeon Park’s supplied research profile documents scholarly publications and citation activity, alongside a 2026 study on post-occupancy evaluation of relocatable modular educational facilities. The publication topic offers a practical perspective on evaluating adaptable construction after occupation. Further conclusions about research quality and impact should rely on the complete article, independently verified bibliographic information, and transparent award assessment criteria.

References

  1. Elsevier. (n.d.). Scopus author details: Soyeon Park, Author ID 57213917853. Scopus. The supplied author profile is the source for the bibliometric figures reported in this article; figures may change as the database is updated.
    https://www.scopus.com/authid/detail.uri?authorId=57213917853
  2. Nguyen, T. D. H. N., Park, S., Jeong, J., & Ahn, Y. (2026). Post occupancy evaluation of the relocatable modular construction method for temporary educational facilities. Engineering, Construction and Architectural Management.
  3. Global Innovation Technologist Awards. (n.d.). Official awards website.
    innovationtechnologist.com

Obaid Ullah Shah | Agricultural and Biological Sciences | Best Academic Researcher Award

Published on by Innovation Technologist

Best Academic Researcher Award

Obaid Ullah Shah
Shanghai Jiao Tong University, China

Obaid Ullah Shah
Affiliation Shanghai Jiao Tong University
Country China
Scopus ID 58627357300
Documents 9
Citations 76
h-index 5
Subject area Agricultural and Biological Sciences
Event Global Innovation Technologist Awards

Obaid Ullah Shah is a researcher affiliated with Shanghai Jiao Tong University, China, whose documented scholarly work includes research in agricultural and biological sciences. His publication, “Identification and expression profiling of the GRAS gene family reveals candidate genes for enhancing abiotic stress tolerance in lentil,” addresses plant molecular biology and the investigation of genetic factors associated with environmental stress responses. His profile provides a basis for examining publication activity, citation indicators and the potential scientific relevance of his research. The available bibliographic information identifies the article as published in BMC Plant Biology in 2026. [1]

Abstract

This article presents a scholarly profile of Obaid Ullah Shah and discusses the relevance of his reported research in agricultural and biological sciences. His identified publication investigates the GRAS gene family and candidate genes potentially associated with abiotic stress tolerance in lentil. Such research is relevant to understanding plant development and responses to environmental conditions. The supplied Scopus metrics record nine documents, 76 citations and an h-index of five. These indicators describe selected aspects of scholarly output and citation activity; they do not independently establish research quality or award eligibility. [1]

Keywords

Obaid Ullah Shah; agricultural sciences; biological sciences; GRAS gene family; lentil; abiotic stress tolerance; plant molecular biology; research impact; academic recognition.

Introduction

Plant responses to drought, salinity, temperature variation and other environmental stresses are important subjects in agricultural research. Understanding the genetic mechanisms associated with these responses can support further investigation into crop resilience and productivity. Research examining gene families and their expression patterns contributes to identifying candidate genes for subsequent functional studies. Shah’s identified publication addresses this scientific area through an investigation of GRAS genes in lentil. [1]

Research Profile

The supplied profile associates Shah with Shanghai Jiao Tong University in China and classifies his subject area as Agricultural and Biological Sciences. The available bibliometric summary lists nine documents, 76 citations and an h-index of five. These values should be interpreted in the context of the database, author identification and date of retrieval. An ORCID identifier was not supplied and therefore cannot be independently matched to the researcher using the provided information.

Research Contributions

The identified study focuses on GRAS transcription factor genes and their expression profiles in lentil. Investigating these genes can help researchers formulate hypotheses about plant growth, development and responses to abiotic stress. Candidate genes identified through profiling require further experimental validation before their functions or practical applications can be established. The article’s stated research focus is therefore relevant to molecular approaches in crop improvement, without implying that specific agricultural outcomes have already been demonstrated. [1]

Publications

The supplied bibliographic record identifies the following publication:

  • Identification and expression profiling of the GRAS gene family reveals candidate genes for enhancing abiotic stress tolerance in lentil. Fawad Ali, Yiren Zhao, Obaid Ullah Shah and colleagues, including Li Liao and Zhiyong Wang. BMC Plant Biology, 2026. [1]

Research Impact

The reported 76 citations indicate that the indexed documents have received scholarly attention, while the h-index of five reflects a combination of publication and citation activity. Citation counts vary across databases and change over time. A balanced assessment should also consider methodological rigor, authorship contributions, reproducibility, research collaboration and the relevance of findings to agricultural challenges. [2]

Award Suitability

The research topic and supplied bibliometric indicators provide relevant information for consideration under the Best Academic Researcher Award associated with the Global Innovation Technologist Awards. A comprehensive assessment should verify the publication record, the researcher’s contribution to the cited work and the accuracy of the metrics. This profile does not represent confirmation that an award has been granted or that an independent selection committee has completed its evaluation.

Conclusion

Obaid Ullah Shah’s identified publication addresses a relevant question in plant molecular biology: the investigation of GRAS genes as candidates for understanding abiotic stress tolerance in lentil. His reported bibliometric indicators provide a concise overview of scholarly activity. Verification of the underlying records and consideration of research quality, originality and contribution remain important for a fair academic recognition process.

References

  1. Ali, F., Zhao, Y., Shah, O. U., et al. (2026). Identification and expression profiling of the GRAS gene family reveals candidate genes for enhancing abiotic stress tolerance in lentil. BMC Plant Biology.
  2. Elsevier. (n.d.). Scopus author details: Obaid Ullah Shah, Author ID 58627357300. Scopus. Author-level bibliometric indicators should be interpreted alongside publication context and database coverage.
    https://www.scopus.com/authid/detail.uri?authorId=58627357300
  3. BMC Plant Biology. (n.d.). Journal website and published research articles. Springer Nature.
  4. Global Innovation Technologist Awards. (n.d.). Official awards website. Award information and eligibility details should be checked against the official event website.
    innovationtechnologist.com