Anton Kazantsev | Space Exploration and Astronomy | Biomedical Science Award

Published on by New Scientists

Biomedical Science Award

Anton Kazantsev

Ministry of Defence of the Russian Federation, Russia

Anton Kazantsev
Affiliation Ministry of Defence of the Russian Federation
Country Russia
Scopus ID 58450862700
Documents 200
Citations 1,337
h-index 17
Subject Area Space Exploration and Astronomy
Event New Scientists Awards
ORCID 0000-0002-1115-609X

Anton Kazantsev is identified in the supplied researcher information with the Ministry of Defence of the Russian Federation in Russia. These bibliometric figures are presented as supplied and should be verified against the current Scopus author record before publication. [1]

This article presents a structured academic recognition profile associated with the Biomedical Science Award and the New Scientists Awards. No specific award outcome, individual publication titles, research findings or biomedical specialization have been independently established by the information provided. [2]

Abstract

This academic recognition profile summarizes the supplied institutional affiliation, subject area and bibliometric indicators associated with Anton Kazantsev. The available information identifies the Ministry of Defence of the Russian Federation as the affiliation and Russia as the country. The reported Scopus indicators are 200 documents, 1,337 citations and an h-index of 17. These values provide a quantitative snapshot of indexed scholarly output and citation activity but do not independently establish the quality, originality or practical significance of individual contributions. [1]

The page is organized around the Biomedical Science Award title supplied for the profile and the New Scientists Awards event. Since detailed publication records, verified research findings and award-decision documentation were not supplied, the article distinguishes provided profile data from research claims requiring further documentary verification. [2]

Keywords

Anton Kazantsev; Biomedical Science Award; New Scientists Awards; academic recognition; research assessment; Scopus author profile; bibliometrics; citation analysis; h-index; Space Exploration and Astronomy; Russian Federation.

Introduction

Academic researcher profiles bring together information about institutional affiliation, scholarly output, citation performance and persistent researcher identifiers. Bibliographic databases such as Scopus provide author-level records that can support the discovery and quantitative examination of indexed publications. Such records should be interpreted carefully because author identification, database coverage, citation practices and subject-specific publishing patterns can influence reported metrics. [1] [4]

This article uses the information supplied for Anton Kazantsev to create a referenceable profile associated with the Biomedical Science Award. The provided subject classification is Space Exploration and Astronomy.

Research Profile

The supplied profile associates Anton Kazantsev with the Ministry of Defence of the Russian Federation in Russia. The Scopus author identifier provided for the researcher is 58450862700, and the supplied ORCID iD is 0000-0002-1115-609X. These identifiers provide separate routes for locating researcher records and checking identity-related metadata. [1] [2]

The subject area supplied for this profile is Space Exploration and Astronomy. The information available for this page does not identify particular laboratories, research projects, technical methods, datasets or verified scientific discoveries. Specific research themes should therefore be added only after examining publications or other primary records attributable to the researcher.

Research Contributions

A reliable account of a researcher’s contributions requires examination of identifiable scholarly outputs and the findings reported in those outputs. The profile data supplied for this article establish bibliometric figures and an indicated subject area, but do not include the titles, abstracts or full texts of individual publications. Accordingly, no specific discovery, invention, experimental result or operational application is attributed to Anton Kazantsev here.

To document research contributions accurately, the following evidence would be relevant:

  • Verified publication records that can be matched to the researcher’s Scopus author profile and ORCID record. [1] [2]
  • Publication abstracts and full texts establishing the research questions, methods, results and stated limitations.

Publications

The supplied information reports 200 documents associated with the Scopus author profile. This figure is presented as user-provided information and has not been independently confirmed as a current database count. The exact publication list, document types, author order, journal details and publication dates should be checked against the live author record before being reproduced in a definitive bibliography. [1]

For each publication, attribution should be checked using multiple available indicators, including author names, institutional affiliations, persistent identifiers and the publication record itself. ORCID provides a persistent researcher identifier, while Scopus provides a database-specific author profile; neither identifier alone guarantees that every associated record is correctly attributed. [1] [2]

Research Impact

The supplied bibliometric indicators are 1,337 citations and an h-index of 17, alongside 200 documents. If confirmed against the current Scopus record, these measures would describe aspects of the indexed publication and citation history associated with the author profile. Citation totals reflect recorded references from other works, while the h-index combines publication output and citation thresholds into a single indicator. [1] [4]

Bibliometric indicators are not direct measures of research quality, societal benefit, methodological rigor or an individual’s contribution to collaborative work. Comparisons between researchers require attention to career stage, disciplinary citation practices, publication types, database coverage and the date on which metrics were collected. Responsible assessment therefore combines quantitative indicators with qualitative examination of research outputs and their documented influence. [4] [5]

Award Suitability

The supplied award title is Biomedical Science Award, and the named event is New Scientists Awards. An academic recognition assessment ordinarily benefits from verifiable evidence of scholarly contributions, originality, research quality, publication record and documented impact. Bibliometric measures may provide supporting context, but they do not independently demonstrate that a nominee satisfies specific award criteria. [4] [5]

The profile data alone do not establish whether Anton Kazantsev has been nominated, shortlisted, selected or formally recognized as a winner. No award outcome is asserted in this article. Before publication as an award-recipient profile, the organizer’s official decision, award category, award year and any associated announcement should be verified using a primary source. The official event website is available through the New Scientists Awards domain. [3]

Conclusion

This profile records the supplied information for Anton Kazantsev, including the stated institutional affiliation, country, subject area, Scopus author identifier, ORCID iD and bibliometric indicators. The figures of 200 documents, 1,337 citations and an h-index of 17 provide a quantitative starting point for a fuller academic profile, subject to confirmation against the relevant database record. [1] [2]

A complete evidence-based account of the researcher’s work would require verified publications, specific research findings and reliable documentation of any award outcome. Until these materials are available, the article avoids attributing unverified discoveries, biomedical expertise or award status to the researcher. This approach supports accurate academic communication and transparent recognition practices.

References

  1. Elsevier. (n.d.). Scopus author details: Anton Kazantsev, Author ID 58450862700.
    https://www.scopus.com/authid/detail.uri?authorId=58450862700
  2. ORCID. (n.d.). ORCID record: 0000-0002-1115-609X.
    https://orcid.org/0000-0002-1115-609X
  3. New Scientists Awards. (n.d.). Official award website.
    https://newscientists.net/
  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.
    https://doi.org/10.1073/pnas.0507655102
  5. Hicks, D., Wouters, P., Waltman, L., de Rijcke, S., & Rafols, I. (2015). Bibliometrics: The Leiden Manifesto for research metrics. Nature, 520, 429–431.
    https://doi.org/10.1038/520429a

Md Razzab Ali | Sustainable Agriculture and Food Security | Best Researcher Award

Published on by New Scientists

Best Researcher Award

Md Razzab Ali
Bangladesh Agricultural Research Institute, Bangladesh

Md Razzab Ali
Affiliation Bangladesh Agricultural Research Institute
Country Bangladesh
Google Scholar ID ZZ1osfMAAAAJ
Documents 8
Citations 372
h-index 12
Subject Area Sustainable Agriculture and Food Security
Event New Scientists Awards
ORCID 0000-0003-1611-9113
Scopus 57219385677

Md Razzab Ali is a researcher affiliated with the Bangladesh Agricultural Research Institute in Bangladesh.His academic profiles provide identifiers for locating his research outputs and citation records across scholarly databases. [1] [2]  The listed publication and citation counts are reported profile data and should be interpreted in relation to the database and date on which they were retrieved. [1] [4]

Abstract

This article presents an academic recognition profile of Md Razzab Ali, affiliated with the Bangladesh Agricultural Research Institute, Bangladesh. These figures offer a quantitative snapshot of the scholarly record associated with the researcher, although citation indicators may vary between databases and over time. [1] [2]

The profile consolidates publicly accessible research identifiers and institutional information to support discovery and verification. It also outlines the relevance of sustainable agriculture and food security as a research domain. Detailed claims about individual experiments, specific publications, or measurable agricultural outcomes require verification against the corresponding original research records and are therefore not inferred solely from the profile information. [3]

Keywords

Md Razzab Ali; sustainable agriculture; food security; agricultural research; agricultural sustainability; research impact; bibliometrics; scholarly publications; Bangladesh Agricultural Research Institute; Best Researcher Award.

Introduction

Sustainable agriculture and food security are closely connected research priorities involving agricultural production, environmental stewardship, efficient resource use, and reliable access to food. Agricultural research can contribute to these priorities through the development and evaluation of production practices, crop-management strategies, improved resource utilization, and evidence-based approaches to food-system resilience. The relevance of any individual contribution depends on the research question, methods, findings, and validation reported in the underlying scholarly literature. [3]

Md Razzab Ali is identified in the supplied profile as affiliated with the Bangladesh Agricultural Research Institute. The institution provides the organizational context for his research profile, while his ORCID and Scopus author record offer identifiers that can help distinguish and retrieve scholarly outputs. His Google Scholar profile provides an additional route for examining indexed publications and citation information. [1] [2]

Research Profile

The available profile information identifies sustainable agriculture and food security as the researcher’s subject area. These fields encompass scientific and practical approaches to maintaining agricultural productivity while addressing environmental constraints and the nutritional needs of populations. Research within this broad domain may include crop production, soil and water management, climate resilience, agricultural technologies, resource efficiency, and food-system sustainability. These topics describe the wider field rather than verified individual specializations of the researcher. [3]

 Because these platforms use different coverage and matching methods, publication records and citation metrics may not be identical across services. [1] [2] [4]

Research Contributions

The researcher’s stated subject area is relevant to agricultural science and the broader objective of strengthening food security. Research in this area can inform the assessment of agricultural practices, productivity constraints, sustainable resource use, and the resilience of farming systems. Establishing the specific contribution of an individual researcher, however, requires examination of the methods, datasets, findings, and conclusions documented in their publications. [3]

The broader research domain includes several important lines of inquiry:

  • Sustainable agricultural production, including the evaluation of practices intended to maintain productivity while using natural resources responsibly.
  • Food security research, which examines the availability, access, utilization, and stability of food supplies.

These areas represent the wider scientific context of sustainable agriculture and food security. They should not be interpreted as a verified list of projects completed by Md Razzab Ali without supporting publication-level evidence.

Publications

The supplied profile reports eight documents associated with the researcher and provides links to his Google Scholar and Scopus profiles. These platforms can be consulted to identify publication titles, co-authors, journal or conference details, publication dates, abstracts, and available digital object identifiers. [1] [2]

A publication-level bibliography should be prepared from verified records rather than reconstructed from incomplete profile information. No individual article titles, author lists, journal names, publication years, or DOI identifiers have been supplied for this page.

For a reliable publication audit, the following details should be checked against the original records:

  • The complete article title and the names of all authors.
  • The journal or conference title, publication year, volume, issue, and page range where applicable.

Research Impact

The h-index is a bibliometric indicator that summarizes publication output and citation frequency by identifying the largest number of publications with at least that number of citations. Neither indicator alone measures methodological quality, practical effectiveness, or the societal value of research. [1] [2]

Research impact in sustainable agriculture and food security may also be evaluated through the reproducibility of findings, relevance to agricultural challenges, adoption of validated practices, contribution to scientific understanding, and demonstrated benefits for farming or food systems. Establishing such impact requires evidence from individual studies and, where relevant, independent evaluations. The available numerical indicators provide a starting point for profile discovery but are not sufficient to establish these broader outcomes.[1] [2]

Award Suitability

The Best Researcher Award profile recognizes the academic record of Md Razzab Ali in the context of the supplied affiliation and stated research subject area. Sustainable agriculture and food security constitute a relevant scientific domain for recognition because research in these fields addresses agricultural sustainability, resource management, and the resilience of food systems.

A rigorous assessment of award suitability should consider multiple forms of evidence rather than relying exclusively on citation counts. Relevant evaluation criteria may include:

  1. Originality and scientific rigor of the research.
  2. Quality, relevance, and verifiability of peer-reviewed publications.
  3. Significance of research findings for sustainable agriculture and food security.

 Any official award status should be confirmed through the award organizer’s published records. [5]

Conclusion

Md Razzab Ali is identified in the supplied information as a researcher affiliated with the Bangladesh Agricultural Research Institute in Bangladesh, with a stated subject area of sustainable agriculture and food security.

These details provide a structured starting point for examining his scholarly record and its relationship to agricultural research. A comprehensive evaluation of his research contributions and suitability for recognition should additionally rely on verified publications, original research findings, and independently assessable evidence of scientific or practical impact. The New Scientists Awards website provides the relevant organizational reference for the award context. [5]

References

  1. Elsevier. (n.d.). Scopus author details: Md Razzab Ali, Author ID 57219385677. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57219385677
  2. Google. (n.d.). Md Razzab Ali: Google Scholar citations profile. Google Scholar.
    https://scholar.google.com/citations?user=ZZ1osfMAAAAJ&hl=en
  3. Food and Agriculture Organization of the United Nations. (n.d.). Sustainable food and agriculture. FAO.
  4. ORCID. (n.d.). Md Razzab Ali: ORCID researcher record, 0000-0003-1611-9113. ORCID.
    https://orcid.org/0000-0003-1611-9113
  5. New Scientists Awards. (n.d.). Official award website.
    https://newscientists.net/

Ronnie Serfa Juan | Artificial Intelligence and Machine Learning | Innovative Research Award

Published on by New Scientists

Innovative Research Award

Ronnie Serfa Juan

Oak Ridge Institute for Science and Education, United States

Ronnie Serfa Juan
Affiliation Oak Ridge Institute for Science and Education
Country United States
Google Scholar ID ZA9OwfwAAAAJ
Documents 30
Citations 506
h-index 9
Subject Area Artificial Intelligence and Machine Learning
Event New Scientists Awards
ORCID 0000-0002-8551-8057
Scopus  57189444986

Ronnie Serfa Juan is a researcher affiliated with the Oak Ridge Institute for Science and Education in the United States.These bibliometric indicators provide a quantitative snapshot of indexed research output and citation activity; they should be interpreted in the context of publication history, subject-area practices, and database coverage. [1] [2]

Abstract

This article presents a bibliographic and research-profile overview of Ronnie Serfa Juan, whose supplied researcher information identifies an affiliation with the Oak Ridge Institute for Science and Education and a subject area of artificial intelligence and machine learning. The profile includes 30 documents, 506 citations, and an h-index of 9, as reported in the provided data. Researcher identifiers from ORCID, Scopus, and Google Scholar offer pathways for examining author identity and indexed scholarly records. [1] [2] [3] The available information supports a concise bibliometric overview, but does not by itself establish specific research findings, individual publication titles, or award decisions.

Keywords

Ronnie Serfa Juan; artificial intelligence; machine learning; research profile; bibliometrics; scholarly publications; citation analysis; ORCID; Scopus; Google Scholar; Innovative Research Award; New Scientists Awards.

Introduction

Artificial intelligence and machine learning encompass computational methods for learning from data, identifying patterns, making predictions, and supporting decision-making. Research in these fields spans methodological development and applications across scientific and technical disciplines.

The profile summarized here uses the researcher name, institutional affiliation, subject area, and bibliometric figures supplied for this article. ORCID provides a persistent researcher identifier, while Scopus and Google Scholar provide author-profile and scholarly discovery services. These sources can assist readers in locating relevant records and checking the consistency of available metadata. [1] [2] [3]

Research Profile

The supplied profile associates Ronnie Serfa Juan with the Oak Ridge Institute for Science and Education in the United States and identifies artificial intelligence and machine learning as the relevant subject area.

The reported metrics are summarized below.

Bibliometric figures can differ across databases because of variations in coverage, duplicate records, author-name disambiguation, document types, and update schedules. The figures above are reproduced from the supplied information and should not be treated as independently verified live counts. [1] [2] [4]

Research Contributions

Artificial intelligence and machine learning research may involve algorithm development, model evaluation, data processing, statistical learning, computational experimentation, or the application of predictive systems to domain-specific problems. However, the subject-area label alone does not establish which of these activities Ronnie Serfa Juan has undertaken. Specific contributions should be described only after examining attributable publications, their methods, reported results, and supporting evidence.

A reliable assessment of research contributions would examine the following evidence:

  • Originality of the research question, method, model, or technical approach.
  • Methodological rigor, including suitable baselines, validation procedures, and reproducibility.
  • Quality and relevance of the evidence supporting reported findings.

Publications

The supplied profile reports 30 documents. A complete publication bibliography, including article titles, co-authors, publication venues, publication years, and DOI identifiers, was not included in the source information provided for this page. Accordingly, no individual paper titles or DOI numbers are asserted here.

Readers can consult the researcher’s Google Scholar profile and Scopus author profile to identify available records. Individual entries should be checked for author attribution, publication status, and DOI accuracy before inclusion in a formal bibliography. [1] [2]

Research Impact

The reported 506 citations and h-index of 9 provide quantitative indicators of the visibility and citation distribution of the researcher’s indexed output. Citation measures can help describe scholarly attention, but they do not directly measure methodological quality, originality, societal benefit, or the independent significance of a particular finding. Interpretation should account for field-specific citation practices, publication age, collaboration patterns, and database coverage. [4]

A fuller evaluation of impact would combine bibliometric evidence with a qualitative review of selected publications, documented methodological advances, subsequent use by other researchers, and independently verifiable applications. No specific downstream applications or societal outcomes are asserted in this profile because supporting evidence was not provided.

Award Suitability

The Innovative Research Award is the recognition category specified for this article under the New Scientists Awards. A research profile in artificial intelligence and machine learning, accompanied by reported publication and citation indicators, may provide useful background for an award assessment. Nevertheless, bibliometric measures alone are insufficient to establish eligibility, originality, or award merit.

A balanced assessment would consider documented research novelty, methodological rigor, publication evidence, the applicant’s specific contribution, reproducibility, and the relevance of the work to the award’s published criteria. The designation of the award category on this page is not, by itself, confirmation that an award has been conferred or that a selection decision has been made. Readers should consult the New Scientists Awards website for official event and award information.

Conclusion

The available information identifies Ronnie Serfa Juan with the Oak Ridge Institute for Science and Education in the United States and lists artificial intelligence and machine learning as the subject area. The supplied bibliometric snapshot reports 30 documents, 506 citations, and an h-index of 9. ORCID, Scopus, and Google Scholar provide starting points for further verification of researcher identity and publication records. A defensible assessment of individual research contributions and suitability for the Innovative Research Award requires examination of the underlying publications and supporting evidence.

References

  1. Elsevier. (n.d.). Scopus author details: Ronnie Serfa Juan, Author ID 57189444986. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57189444986
  2. Google. (n.d.). Ronnie Serfa Juan: Google Scholar author profile. Google Scholar.
    https://scholar.google.com/citations?user=ZA9OwfwAAAAJ&hl=en&oi=ao
  3. ORCID. (n.d.). Ronnie Serfa Juan: ORCID researcher record. ORCID.
    https://orcid.org/0000-0002-8551-8057
  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.
    https://doi.org/10.1073/pnas.0507655102
  5. New Scientists Awards. (n.d.). Official award website. New Scientists Awards.
    https://newscientists.net/

Meng Qinghe | Health and Medicine Advances | Best Researcher Award

Published on by New Scientists

Best Researcher Award

Meng Qinghe
SUNY Upstate Medical University, United States

Meng Qinghe
Affiliation SUNY Upstate Medical University
Country United States
Google Scholar ID ndrO-48AAAAJ
Documents 29
Citations 1,600
h-index 23
Subject Area Health and Medicine Advances
Event New Scientists Awards
ORCID 0000-0002-1526-1380
Scopus  59607689300

Meng Qinghe is presented in this academic recognition profile in connection with the Best Researcher Award and the subject area of health and medicine advances. The supplied profile information identifies an affiliation with SUNY Upstate Medical University in the United States and provides researcher identifiers and bibliometric figures for reference. These details establish the basis of this profile, while specific research interests, individual publications, and award evaluation outcomes require verification against authoritative academic records. [1] [2]

Abstract

Meng Qinghe, associated with SUNY Upstate Medical University in the United States. The profile records the supplied researcher identifiers, bibliometric indicators, subject classification, and connection to the New Scientists Awards.  These metrics offer quantitative indicators of indexed research output and citation activity but do not independently establish research quality, clinical significance, or award eligibility. The Google Scholar and Scopus records provide starting points for verifying the underlying bibliographic information. [1] [2]

Keywords

Meng Qinghe; Best Researcher Award; SUNY Upstate Medical University; health and medicine advances; medical research; scholarly publications; citation analysis; Google Scholar; Scopus; ORCID; New Scientists Awards.

Introduction

Academic recognition profiles document a researcher’s institutional association, scholarly record, and potential relevance to a defined scientific field. In health and medicine, research assessment may consider publication quality, methodological rigor, reproducibility, clinical relevance, collaboration, and the contribution of research to existing knowledge. Bibliometric measures can complement these considerations, but they should be interpreted alongside the content and context of the work. [3]

This profile uses the researcher details supplied for Meng Qinghe. The identifiers listed below support further investigation of the academic record. No specific research findings, clinical outcomes, or publication titles are attributed to the researcher here without independently verified supporting records.

Research Profile

The supplied information associates Meng Qinghe with SUNY Upstate Medical University, a United States institution, and identifies health and medicine advances as the relevant subject area for this recognition profile. The listed Google Scholar profile and Scopus author record can be consulted to investigate publication metadata, citation activity, and subject-specific research output. [1] [2]

Bibliometric figures may vary between databases and over time because of differences in coverage, author disambiguation, document indexing, and citation updates. The reported values should therefore be treated as supplied profile data rather than as independently confirmed live measurements.

Research Contributions

The specific scientific contributions of Meng Qinghe cannot be reliably characterized from the supplied identifiers and aggregate bibliometric figures alone.  The Scopus and Google Scholar profiles are relevant starting points for identifying publications associated with the researcher. [1] [2]

A comprehensive assessment of contributions in health and medicine may examine the following dimensions when supported by documented research:

  • Originality and significance of the research questions addressed.
  • Appropriateness of study design, analytical methods, and validation procedures.
  • Relevance of findings to biomedical knowledge, healthcare practice, or future research.

These are general assessment criteria, not claims that any particular achievement has been established for the researcher.

Publications

The supplied profile reports 29 documents. A verified publication list would require checking the associated author records and confirming that each item belongs to the same researcher. Relevant bibliographic details include publication title, author list, journal or conference, year, volume, issue, page range, and DOI where available. [1] [2]

 The absence of individual citations here should not be interpreted as evidence that the researcher has no relevant publications.

Research Impact

The h-index is a citation-based measure reflecting the number of publications that have each received at least the corresponding number of citations. Its interpretation depends on database coverage, publication history, disciplinary citation practices, and the accuracy of author attribution. [3]

Citation totals can indicate scholarly attention, but they do not by themselves demonstrate methodological quality, originality, clinical effectiveness, or direct benefits to patients. A balanced evaluation should also examine individual publications, the nature of their influence, independent validation, and the context in which citations occur. The reported indicators are therefore best treated as components of a broader research assessment rather than definitive measures of overall scientific merit.

Award Suitability

The Best Researcher Award profile recognizes the supplied academic information associated with Meng Qinghe and the subject area of health and medicine advances. The reported publication and citation indicators may be relevant to a research assessment, provided that they are confirmed against the appropriate author records and evaluated in context.

A defensible award evaluation would consider documented original contributions, publication quality, research integrity, scholarly influence, and relevance to the award’s published eligibility criteria. Institutional affiliation and bibliometric figures alone are insufficient to establish an award decision.

Further information about the organizing website and its award activities is available through the official New Scientists Awards website. [4]

Conclusion

This academic profile documents the supplied details for Meng Qinghe, including the institutional association with SUNY Upstate Medical University, the health and medicine advances subject classification, researcher identifiers, and reported bibliometric figures. The linked Google Scholar, Scopus, and ORCID records provide resources for further verification. A more comprehensive evaluation of research contributions and suitability for the Best Researcher Award would require examination of the researcher’s verified publications, substantive scientific findings, and the relevant award criteria.

References

  1. Elsevier. (n.d.). Scopus author details: Meng Qinghe, Author ID 59607689300.
    https://www.scopus.com/authid/detail.uri?authorId=59607689300
  2. Google Scholar. (n.d.). Meng Qinghe: Google Scholar author profile.
    https://scholar.google.com/citations?user=ndrO-48AAAAJ&hl=en&oi=ao
  3. 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.
    https://doi.org/10.1073/pnas.0507655102
  4. New Scientists Awards. (n.d.). Official website.
    https://newscientists.net/
  5. ORCID. (n.d.). ORCID record supplied for Meng Qinghe.
    https://orcid.org/0000-0002-1526-1380

Dongyang Wang | Nanotechnology and Materials Science | Best Researcher Award

Published on by New Scientists

Best Researcher Award

Dongyang Wang

Jiangsu University of Science and Technology, China

Dongyang Wang
Affiliation Jiangsu University of Science and Technology
Country China
Scopus ID 57197780043
Documents 28
Citations 1,064
h-index 17
Subject Area Nanotechnology and Materials Science
Event New Scientists Awards
ORCID 0009-0009-1574-1913

Dongyang Wang is a researcher affiliated with Jiangsu University of Science and Technology, China. The researcher’s designated subject area is Nanotechnology and Materials Science, a broad field encompassing nanoscale materials, materials characterization, engineering applications, and the development of advanced functional materials. These bibliometric indicators provide a quantitative overview of the indexed author profile and form part of the academic background presented for the Best Researcher Award associated with New Scientists Awards. [1] [2]

Abstract

Dongyang Wang, affiliated with Jiangsu University of Science and Technology in China, with a subject-area designation of Nanotechnology and Materials Science. These indicators describe aspects of scholarly productivity and citation activity within the indexed author record. The article places the profile in the context of the Best Researcher Award associated with New Scientists Awards and outlines the relevance of bibliometric indicators to academic recognition. The profile should therefore be read as a structured summary of the provided researcher information rather than an independent assessment of the researcher’s complete academic record. [1] [2]

Keywords

Dongyang Wang; Jiangsu University of Science and Technology; China; Nanotechnology and Materials Science; nanomaterials; advanced materials; bibliometrics; Scopus; citation analysis; h-index; Best Researcher Award; New Scientists Awards.

Introduction

Nanotechnology and Materials Science encompass research into the structure, properties, synthesis, characterization, and application of materials, including systems designed and studied at the nanoscale. Research in these areas can contribute to advances in materials engineering, electronics, energy technologies, coatings, and other application domains.

Bibliographic databases provide tools for identifying scholarly documents and examining citation relationships. Scopus assigns author identifiers and provides publication-related indicators that can help readers review indexed research activity. Such indicators require careful interpretation because database coverage, author-name disambiguation, publication type, and citation practices can influence the resulting figures. [1] [3]

This article summarizes the information supplied for Dongyang Wang and organizes it into a research profile relevant to the Best Researcher Award category. It distinguishes reported bibliometric information from claims about individual scientific achievements that require additional primary-source verification.

Research Profile

Dongyang Wang is listed in the supplied information as being affiliated with Jiangsu University of Science and Technology, China. The stated subject area is Nanotechnology and Materials Science. The profile is associated with Scopus author identifier 57197780043 and ORCID identifier 0009-0009-1574-1913. These identifiers provide direct routes to the relevant author and researcher records, where available publication metadata and identity details can be examined. [1] [4]

The bibliometric values provided for this article are summarized in the following table. They represent the supplied profile figures and are not presented as independently verified live statistics. Citation counts and h-index values may change as records are added, citation links are updated, or author profiles are corrected.

Research Contributions

The supplied subject-area designation places Dongyang Wang’s profile within Nanotechnology and Materials Science. This field includes diverse lines of investigation, such as nanostructured materials, material synthesis, surface engineering, physical and chemical characterization, and the development of materials for practical applications.

A comprehensive account of research contributions would require examination of verified publications, their stated objectives, methods, findings, and subsequent scholarly use. The following elements would support a more detailed and evidence-based assessment:

  • Documented research problems and original questions addressed in published studies.
  • Materials, experimental methods, computational approaches, and characterization techniques explicitly described in the research.

Publications

The supplied Scopus profile reports 28 documents associated with Dongyang Wang. The input data do not provide individual publication titles, journal names, author lists, publication years, or DOI identifiers. Accordingly, this article does not invent a publication list or attribute specific experimental results to the researcher. Readers can consult the linked Scopus author profile to review the indexed documents and associated citation information. [1]

For a publication-ready bibliography, each record should be checked against the publisher’s official page or its DOI landing page. Recommended metadata include the full article title, all listed authors, journal or proceedings title, publication year, volume, issue, page range or article number, and DOI where available. Crossref offers a searchable metadata service that can help locate and verify publication records. [5]

Research Impact

The supplied profile reports 1,064 citations and an h-index of 17. Under the conventional definition of the h-index, a value of 17 means that at least 17 documents in the relevant publication set have each received at least 17 citations, provided the profile data and citation records are accurate. The reported citation total represents the aggregate citation figure supplied for the indexed author profile. These indicators describe citation activity but do not independently establish research quality, originality, reproducibility, or real-world impact. [1] [2]

Bibliometric measures can vary according to database coverage, disciplinary citation patterns, career stage, co-authorship practices, and the types of documents included. A balanced assessment of research impact should therefore consider quantitative indicators alongside expert evaluation of the publications, methodological rigor, originality, research integrity, and documented influence on subsequent work or practical applications. The figures presented here should be interpreted as the values supplied for this article, not as a live or independently audited assessment.

Award Suitability

The Best Researcher Award is the recognition category associated with this article through New Scientists Awards. The supplied profile provides bibliometric information that may be relevant to an academic recognition summary, including the number of indexed documents, citations, and h-index. The Scopus author identifier and ORCID record also provide starting points for checking researcher identity and publication metadata. [1] [4]

Bibliometric statistics alone are insufficient to determine award eligibility or establish the merits of a researcher’s contributions. A thorough assessment would also require verified publications, evidence of originality and methodological quality, documented research outcomes, and alignment with the award’s published criteria. This profile identifies the recognition category associated with the article but does not independently claim that an award has been conferred or that a selection decision has been made.

Conclusion

Dongyang Wang is identified in the supplied information as a researcher affiliated with Jiangsu University of Science and Technology in China, with a subject-area designation of Nanotechnology and Materials Science. These figures offer a concise overview of indexed publication output and citation activity. A detailed evaluation of specific scientific contributions would require examination of verified publications and their original findings. The linked Scopus and ORCID records provide resources for further verification, while New Scientists Awards is the associated academic recognition platform. [1] [4]

References

  1. Elsevier. (n.d.). Scopus author details: Dongyang Wang, Author ID 57197780043.
    https://www.scopus.com/authid/detail.uri?authorId=57197780043
  2. 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.
    https://doi.org/10.1073/pnas.0507655102
  3. Elsevier. (n.d.). Scopus: Abstract and citation database.
    https://www.scopus.com/
  4. ORCID. (n.d.). Dongyang Wang researcher identifier: 0009-0009-1574-1913.
    https://orcid.org/0009-0009-1574-1913
  5. Crossref. (n.d.). Crossref metadata search.
    https://search.crossref.org/

Rasool Norouzi Seyed Hossini | Human-Computer Interaction and User Experience | Best Researcher Award

Published on by New Scientists

Best Researcher Award

Rasool Norouzi Seyed Hossini

Tarbiat Modares University, Iran

Rasool Norouzi Seyed Hossini
Affiliation Tarbiat Modares University
Country Iran
Google Scholar ID gBT2Lb0AAAAJ
Documents 36
Citations 851
h-index 15
Subject Area Human-Computer Interaction and User Experience
Event New Scientists Awards
ORCID 0000-0003-0575-6811
Scopus  57211508333

Rasool Norouzi Seyed Hossini is identified in the supplied profile information as a researcher affiliated with Tarbiat Modares University, Iran. The subject area associated with this academic recognition profile is Human-Computer Interaction and User Experience. These indicators provide a quantitative overview of the researcher’s reported scholarly output and citation activity. The profile is presented in connection with the Best Researcher Award and New Scientists Awards. [1] [2] [3]

Abstract

This article presents an academic recognition profile for Rasool Norouzi Seyed Hossini, whose supplied institutional affiliation is Tarbiat Modares University in Iran. The identified subject area is Human-Computer Interaction and User Experience.These bibliometric indicators describe selected aspects of publication output and citation activity but do not independently establish the quality, originality, or practical impact of individual studies. The article summarizes the supplied profile information, outlines the relevance of research evaluation in human-computer interaction, and identifies resources for further examination of the researcher’s scholarly records. Specific research findings and publication-level claims require confirmation from original publications and their associated metadata. [1] [2] [4]

Keywords

Rasool Norouzi Seyed Hossini; Tarbiat Modares University; Iran; Human-Computer Interaction; user experience; HCI; bibliometrics; Google Scholar; Scopus; ORCID; research impact; Best Researcher Award; New Scientists Awards.

Introduction

Human-Computer Interaction (HCI) examines how people interact with computing systems and how interactive technologies can be designed and evaluated to support user needs. User experience research considers users’ perceptions, responses, and experiences before, during, and after interaction with products or services.The precise research topics associated with an individual researcher should, however, be established from verified publications rather than inferred from a broad subject-area label. [4]

Academic profiles provide a structured way to identify researchers and review publication records. Google Scholar and Scopus offer different forms of scholarly indexing and citation information, while ORCID provides a persistent researcher identifier that can help distinguish individuals with similar names. Their coverage and counting methods differ, so bibliometric values should be interpreted in relation to the source from which they were obtained. [1] [2] [3]

Research Profile

Rasool Norouzi Seyed Hossini is associated in the supplied information with Tarbiat Modares University in Iran. The profile identifies Human-Computer Interaction and User Experience as the relevant subject area.  These identifiers enable readers to consult the respective records and investigate indexed publications, author metadata, and citation information. [1] [2] [3]

The bibliometric values supplied for this article are summarized below. Google Scholar and Scopus may report different document and citation totals because their coverage, indexing practices, and profile-management mechanisms are not identical. The figures below are reproduced as supplied and are not represented as independently verified, synchronized, or live database values.

Research Contributions

Human-computer interaction and user experience research can contribute to the understanding, design, and evaluation of interactive systems. Depending on the subject of a particular study, such contributions may involve usability testing, interaction techniques, interface evaluation, user-centered design methods, accessibility, or empirical analysis of user behavior. These are general areas within the discipline and are not presented here as verified research topics or specific findings attributable to Rasool Norouzi Seyed Hossini.

A detailed account of the researcher’s individual contributions requires examination of the publications associated with the supplied author identifiers. Relevant evidence may include:

  • Research questions and objectives documented in verified journal articles, conference papers, or other scholarly outputs.
  • Methods used to evaluate usability, user experience, interaction design, or other relevant research problems, where applicable.

This evidence-based approach makes it possible to distinguish general disciplinary context from documented individual contributions and supports a more reliable assessment of scholarly work. [4] [5]

Publications

The supplied profile data report 36 documents. The input information does not provide a verified list of publication titles, author order, journals, conference proceedings, publication dates, or DOI identifiers. Accordingly, individual works are not listed here, and no specific research findings are attributed to the researcher without primary-source evidence.

The Google Scholar profile and Scopus author record provide starting points for reviewing indexed publications. For a publication-level bibliography, each record should be checked against the original publisher’s page or a DOI registration record. A complete citation generally includes the authors, title, journal or conference name, year, volume and issue where applicable, page range or article number, and DOI. Crossref offers a searchable scholarly metadata service that can assist in locating publication records and resolving DOI information. [1] [2] [5]

Research Impact

 This interpretation assumes that the supplied value was calculated using the standard definition and the relevant database’s indexed records. [1] [5]

Bibliometric indicators are useful descriptive measures, but they have limitations. Citation patterns vary by discipline, publication type, career stage, database coverage, and scholarly collaboration. Citation counts alone do not demonstrate methodological rigor, originality, reproducibility, or direct impact on users and society. In human-computer interaction, a balanced evaluation may also consider the quality of empirical methods, the relevance of the research questions, the strength of usability or user-experience evidence, and the documented usefulness of resulting methods or systems. [4] [5]

Award Suitability

The Best Researcher Award is the recognition category specified for this profile under New Scientists Awards. The Google Scholar and Scopus identifiers, together with the ORCID record, provide resources for examining researcher identity and locating scholarly outputs. [1] [2] [3]

Bibliometric indicators should be considered alongside qualitative evidence when evaluating research for recognition. Relevant considerations may include the originality and significance of published findings, the rigor of the research methods, the contribution to the field, research integrity, and alignment with the award’s published eligibility and evaluation criteria. The inclusion of this profile does not independently confirm nomination status, award selection, or an official award outcome. Such claims should be supported by an authoritative announcement from the award organizer.

Conclusion

Rasool Norouzi Seyed Hossini is identified in the supplied information as a researcher affiliated with Tarbiat Modares University in Iran, with a subject-area designation of Human-Computer Interaction and User Experience.  These values offer a concise bibliometric overview but should be interpreted in the context of database coverage and the quality of the underlying research. Further analysis of verified publications is necessary to document specific scholarly contributions and their significance. Google Scholar, Scopus, and ORCID provide complementary resources for examining publication records and researcher identity. [1] [2] [3]

References

  1. Google. (n.d.). Google Scholar profile: Rasool Norouzi Seyed Hossini.
    https://scholar.google.com/citations?hl=en&user=gBT2Lb0AAAAJ&view_op=list_works&sortby=pubdate
  2. Elsevier. (n.d.). Scopus author details: Rasool Norouzi Seyed Hossini, Author ID 57211508333.
    https://www.scopus.com/authid/detail.uri?authorId=57211508333
  3. ORCID. (n.d.). Researcher identifier: 0000-0003-0575-6811.
    https://orcid.org/0000-0003-0575-6811
  4. Association for Computing Machinery, Special Interest Group on Computer-Human Interaction. (n.d.). SIGCHI: Computer-Human Interaction.
    https://sigchi.org/
  5. Crossref. (n.d.). Crossref metadata search.
    https://search.crossref.org/

xuebin ling | Health and Medicine Advances | Best Researcher Award

Published on by New Scientists

Best Researcher Award

Xuebin Ling

Hainan Medical University, China

Xuebin Ling
Affiliation Hainan Medical University
Country China
Scopus ID 57824205700
Documents 9
Citations 182
h-index 5
Subject Area Health and Medicine Advances
Event New Scientists Awards
ORCID 0000-0002-3024-3308

Xuebin Ling is identified in the supplied researcher profile as being affiliated with Hainan Medical University in China.The designated subject area for this academic recognition profile is Health and Medicine Advances, and the associated recognition category is Best Researcher Award under New Scientists Awards.  [1] [2]

Abstract

This article presents an academic recognition profile for Xuebin Ling, identified in the supplied information as a researcher affiliated with Hainan Medical University, China. These indicators offer a concise overview of publication output and citation activity within a bibliographic database. The article places the profile in the subject area of Health and Medicine Advances and the recognition context of the Best Researcher Award associated with New Scientists Awards. Specific research findings, individual publication details, and independently verified award decisions are not included in the supplied data; consequently, the discussion avoids attributing unverified scientific contributions to the researcher. [1] [3]

Keywords

Xuebin Ling; Hainan Medical University; China; Health and Medicine Advances; academic research; bibliometrics; Scopus author profile; citation analysis; h-index; scholarly publications; Best Researcher Award; New Scientists Awards.

Introduction

Academic researcher profiles consolidate information about institutional affiliations, scholarly publications, and citation indicators. Bibliographic databases such as Scopus enable users to identify indexed research documents and examine citation relationships associated with author records. Persistent researcher identifiers, including ORCID iDs, can further support author identification and the association of scholarly outputs with individual researchers. [1] [2] [4]

This page documents the supplied academic profile of Xuebin Ling and its association with the Best Researcher Award category. It is intended as a structured biographical and bibliometric overview rather than an independent evaluation of research quality. Citation counts and related metrics should be interpreted alongside publication content, methodological rigor, disciplinary practices, and documented research outcomes. [3]

Research Profile

The supplied information identifies Xuebin Ling as affiliated with Hainan Medical University in China. The stated subject area is Health and Medicine Advances. The associated Scopus author identifier is 57824205700, and the supplied ORCID iD is 0000-0002-3024-3308. These identifiers provide direct starting points for reviewing the researcher’s indexed publications and associated bibliographic records. [1] [4]

The bibliometric information supplied for this article is summarized in the following table. Database metrics may change over time as records are added, citations are indexed, or author profiles are corrected. The values below should therefore be understood as reported figures rather than a live database extract.

Research Contributions

The available profile data establish a limited bibliometric overview but do not identify individual research projects, experimental methods, clinical investigations, datasets, patents, or specific scientific findings attributable to Xuebin Ling.

A publication-based assessment of research contributions could examine the following elements after the relevant records have been verified:

  • The research questions and objectives addressed in the researcher’s published studies.
  • The methods, analytical approaches, study designs, and data sources described in the original publications.

Such documentation would support a more complete account of subject-specific contributions while distinguishing evidence from individual studies from broader bibliometric indicators. [3] [5]

Publications

The supplied Scopus profile information reports nine documents. Individual publication titles, author lists, journal details, publication years, and DOI identifiers were not supplied for this article. Accordingly, no specific papers are listed or attributed to Xuebin Ling without verification. The Scopus author profile provides a starting point for reviewing indexed documents and associated citation records. [1]

A verified bibliography should include the complete title of each work, the authors in the published order, the journal or conference proceedings, the publication year, relevant volume and issue information, page range or article number, and DOI where available. DOI metadata can be checked through Crossref and compared with the publisher’s official record. [5]

Research Impact

The reported citation total of 182 indicates the citation activity associated with the supplied Scopus author profile. The reported h-index of 5 indicates that at least five documents in the relevant indexed record have received at least five citations each, assuming the profile and its underlying records are accurate.[1] [3]

Bibliometric indicators are influenced by disciplinary citation patterns, career stage, database coverage, publication types, and the time elapsed since publication. They should not be interpreted as direct measures of research validity, originality, clinical benefit, or societal impact.  [3]

Award Suitability

The Best Researcher Award is the recognition category specified for this article under New Scientists Awards. The supplied profile provides bibliometric indicators and researcher identifiers that can serve as supporting information in an academic recognition profile. A full assessment of suitability for a research award would require consideration of verified publications, research originality, methodological quality, documented outcomes, and the published eligibility and evaluation criteria of the award organizer. [1] [4]

The information provided for this page does not establish whether the researcher has been nominated, shortlisted, selected, or formally declared a winner. The article therefore records the stated award category without representing an unverified award outcome as fact. Official information about the event and its categories should be checked through the New Scientists Awards website. [5]

Conclusion

Xuebin Ling is identified in the supplied information as a researcher affiliated with Hainan Medical University in China, with the stated subject area of Health and Medicine Advances. The profile reports nine documents, 182 citations, and an h-index of 5. These figures offer a concise bibliometric overview, but a detailed evaluation of research contributions requires examination of verified publications and their findings. [1] [4] [5]

References

  1. Elsevier. (n.d.). Scopus author details: Xuebin Ling, Author ID 57824205700. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57824205700
  2. Elsevier. (n.d.). Scopus. Abstract and citation database for scholarly literature.
    https://www.scopus.com/
  3. 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.
    https://doi.org/10.1073/pnas.0507655102
  4. ORCID. (n.d.). Xuebin Ling researcher record, ORCID iD 0000-0002-3024-3308.
    https://orcid.org/0000-0002-3024-3308
  5. New Scientists Awards. (n.d.). Official awards website.
    https://newscientists.net/

Nazim Manić | Artificial Intelligence and Machine Learning | Best Researcher Award

Published on by New Scientists

Best Researcher Award

Nazim Manić

State University of Novi Pazar, Serbia

Nazim Manić
Affiliation State University of Novi Pazar
Country Serbia
Google Scholar ID s-N_FiAAAAAJ
Documents 4
Citations 42
h-index 3
Subject Area Artificial Intelligence and Machine Learning
Event New Scientists Awards
ORCID 0000-0001-8346-8255
Scopus  57192164885

Nazim Manić is identified in the supplied researcher profile as being affiliated with the State University of Novi Pazar in Serbia. This article presents the information in the context of the Best Researcher Award associated with New Scientists Awards; it does not independently establish an award selection or result. [1] [2] [3]

Abstract

This article provides an academic recognition profile for Nazim Manić, identified in the supplied information as affiliated with the State University of Novi Pazar, Serbia These values summarize selected dimensions of indexed scholarly output and citation activity but do not independently establish research quality, originality, or broader impact. Google Scholar, Scopus, and ORCID are provided as routes for checking researcher identity and available bibliographic records. Since individual publication titles, study findings, and DOI records were not included in the input data, this article avoids attributing specific technical contributions without verification. The profile is presented in connection with the Best Researcher Award category and New Scientists Awards. [1] [2] [3]

Keywords

Nazim Manić; State University of Novi Pazar; Serbia; Artificial Intelligence; Machine Learning; Google Scholar; Scopus; ORCID; bibliometrics; citation analysis; h-index; Best Researcher Award; New Scientists Awards.

Introduction

Researcher profiles and scholarly indexing services help readers identify authors, locate publications, and examine citation relationships. Google Scholar provides a searchable index of scholarly literature and author profiles, while Scopus supplies curated bibliographic and citation information for indexed publications. ORCID provides persistent digital identifiers that help distinguish researchers and connect them with their scholarly activities. Each system has its own coverage and record-management practices, so information may differ between databases. [1] [2] [3]

This article documents the researcher details and bibliometric values supplied for Nazim Manić. It uses a neutral, Wikipedia-inspired structure to distinguish reported profile information from research-specific claims that would require examination of verified publications. The stated association with Artificial Intelligence and Machine Learning provides the subject classification for this profile, rather than a verified inventory of individual research specializations.

Research Profile

Nazim Manić is associated in the supplied data with the State University of Novi Pazar in Serbia. The stated subject area is Artificial Intelligence and Machine Learning, fields encompassing computational methods that support prediction, classification, optimization, data analysis, and automated decision-making.

 These identifiers can be used to locate relevant records, although the publication lists and author metadata should be checked to ensure that they correspond to the same individual. [1] [2] [3]

These values should be treated as a snapshot of the supplied profile information rather than guaranteed current metrics. Citation counts and h-index values can change as new publications are indexed, citation links are updated, and author profiles are corrected. The underlying database should be consulted for the latest figures.

Research Contributions

The supplied information associates the researcher with Artificial Intelligence and Machine Learning but does not identify individual papers, technical methods, software systems, datasets, patents, or specific scientific findings. Consequently, no particular algorithm, application, or research breakthrough is attributed to Nazim Manić in this article without supporting bibliographic evidence.

A publication-based account of research contributions could document the following elements after the relevant records have been verified:

  • Research problems and objectives addressed in the researcher’s verified publications.
  • Machine-learning algorithms, artificial-intelligence methods, computational frameworks, or analytical techniques explicitly described in published work.[4] [5]

Publications

The supplied Google Scholar profile information reports four documents. Individual publication titles, co-authors, journal names, publication years, and DOI identifiers were not supplied for this article. A specific bibliography is therefore not reproduced here, as doing so without verification could introduce incorrect titles or attribute publications to the wrong author.

The Google Scholar and Scopus author profiles are appropriate starting points for identifying potentially relevant records. Each publication should be checked against the publisher’s page or its DOI record before being included in a formal academic bibliography. Crossref provides a searchable metadata service that can help locate DOI-linked publication information. [1] [2] [5]

Research Impact

The reported citation count of 42 indicates that publications associated with the supplied profile have received citations within the relevant indexing context. An h-index of 3 conventionally indicates that at least three publications have each received at least three citations in the database or profile from which the value was calculated. The reported figures should be interpreted in relation to the source, coverage, and date of retrieval. [1] [4]

Citation measures are useful for describing aspects of scholarly visibility, but they do not directly measure methodological rigor, originality, reproducibility, or practical benefit. Citation patterns can vary substantially by discipline, publication type, research collaboration, and career stage.

Award Suitability

The Best Researcher Award is the recognition category specified for this academic profile in connection with New Scientists Awards. The supplied researcher identifiers and bibliometric values provide a starting point for documenting scholarly output and locating records for further review.

An appropriate award assessment would require review of verified research outputs, originality, technical rigor, documented contributions, research integrity, and alignment with the award’s published criteria. Citation counts and h-index values alone are not sufficient to establish award eligibility or merit.. [4]

Conclusion

Nazim Manić is identified in the supplied information as being affiliated with the State University of Novi Pazar in Serbia, with Artificial Intelligence and Machine Learning given as the subject area. Google Scholar, Scopus, and ORCID identifiers provide useful routes for examining author identity and scholarly records. A more comprehensive account of research contributions and impact would require verification of individual publications and their findings..

References

  1. Google. (n.d.). Google Scholar profile: Nazim Manić, user ID s-N_FiAAAAAJ.
    https://scholar.google.com/citations?user=s-N_FiAAAAAJ&hl=en&oi=ao
  2. Elsevier. (n.d.). Scopus author details: Nazim Manić, Author ID 57192164885.
    https://www.scopus.com/authid/detail.uri?authorId=57192164885
  3. ORCID. (n.d.). Nazim Manić researcher identifier: 0000-0001-8346-8255.
    https://orcid.org/0000-0001-8346-8255
  4. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences, 
    https://doi.org/10.1073/pnas.0507655102
  5. Crossref. (n.d.). Crossref metadata search. Crossref provides a searchable service for bibliographic metadata, including DOI-associated publication records. It is included as a verification resource;
    https://search.crossref.org/

Muhammad Noman | Quantum Physics and Quantum Computing | Research Excellence Award

Published on by New Scientists

Research Excellence Award

Muhammad Noman
Ningbo University, China

Muhammad Noman
Affiliation Ningbo University
Country China
Scopus ID 59308497300
Documents 28
Citations 224
h-index 7
Subject Area Quantum Physics and Quantum Computing
Event New Scientists Awards
ORCID 0009-0003-6136-0114
Google Scholar ID mUQqapYAAAAJ

Muhammad Noman is a researcher affiliated with Ningbo University, China, whose documented research profile is associated with quantum physics and quantum computing. His scholarly record comprises 28 documents and 224 citations, with an h-index of 7 in the supplied bibliometric record. These indicators provide a quantitative view of research dissemination and citation impact, while the subject classification identifies a research orientation toward contemporary problems at the intersection of quantum physics and quantum information science. [1]

Abstract

This article presents an academic recognition profile of Muhammad Noman, a researcher affiliated with Ningbo University in China and associated with the subject area of quantum physics and quantum computing. The supplied bibliometric information records 28 scholarly documents, 224 citations, and an h-index of 7. [1] The profile considers these indicators alongside the broader intellectual context of quantum computing, a field that combines principles of quantum mechanics, information theory, and computational science. Foundational work in quantum algorithms established the theoretical basis for computational approaches that differ fundamentally from classical algorithms. [5]

Keywords

Muhammad Noman; Research Excellence Award; Ningbo University; China; Quantum Physics; Quantum Computing; Quantum Information Science; Computational Physics; Scholarly Impact; Research Recognition.

Introduction

Quantum physics and quantum computing constitute closely connected research domains in which physical principles are used to understand, represent, process, and manipulate information. Quantum computation differs from conventional computation through the use of quantum states and operations, creating a theoretical framework for algorithms that can address selected computational problems in ways not directly equivalent to classical approaches. [5]

Within this research environment, academic evaluation commonly considers several complementary dimensions, including publication output, citation activity, h-index, disciplinary relevance, and the coherence of an investigator’s research profile. Bibliometric databases such as Scopus provide structured author-level information that can assist in assessing the visibility and citation history of scholarly work. [1] For Muhammad Noman.

Research Profile

Muhammad Noman is affiliated with Ningbo University in China and is identified in the supplied academic information with a subject focus on quantum physics and quantum computing. His Scopus author identifier is 59308497300, providing a persistent bibliographic reference for the indexed scholarly record. [1]  [2]

Citation counts can vary according to database coverage, publication type, disciplinary practices, publication age, and indexing differences. Google Scholar provides another scholarly discovery and citation environment and can therefore serve as a complementary source when examining an author’s research visibility. [3]

Research Contributions

The documented research profile places Muhammad Noman within quantum physics and quantum computing, two areas that have developed through sustained interaction between fundamental physics, mathematical methods, computer science, and information theory. Research in these fields may address quantum algorithms, quantum information processing, computational models, quantum states, quantum systems, or related theoretical and applied questions.

  • The indexed publication record of 28 documents indicates sustained scholarly activity within the supplied bibliometric profile. [1]
  • The reported 224 citations provide evidence of scholarly use and visibility of the indexed research output, subject to the limitations inherent in citation-based assessment.

The wider field provides an important context for evaluating this profile. Quantum algorithms have demonstrated that quantum computational models can offer fundamentally different approaches to selected computational problems. Shor’s seminal work is one of the best-known examples of this theoretical development. [5]

Publications

The supplied Scopus record identifies 28 documents associated with Muhammad Noman. [1] Because individual publication titles, journal names, publication years, and article-level DOI identifiers were not provided in the source information supplied for this profile, this article does not attribute specific publications to the researcher without independent bibliographic verification.

For disciplinary context, foundational literature demonstrates the significance of quantum algorithms within the broader development of quantum computing. Shor’s 1994 conference paper introduced algorithms for discrete logarithms and factoring on a quantum computer and is associated with DOI 10.1109/SFCS.1994.365700. [5]

Research Impact

The reported 224 citations and h-index of 7 provide quantitative indicators of the visibility of Muhammad Noman’s indexed scholarly output. [1] Citation-based indicators are useful for comparative and descriptive purposes, but they should be considered alongside the nature of the research, publication venues, collaboration patterns, methodological contribution, reproducibility, and influence on subsequent research.

The availability of researcher identifiers through ORCID and Google Scholar further supports scholarly discoverability. ORCID provides a persistent identifier for distinguishing researchers, while Google Scholar offers a broad scholarly search and citation environment. [2] [3]

Award Suitability

The Research Excellence Award profile is supported by the documented combination of disciplinary relevance, scholarly output, citation activity, and researcher identification. Muhammad Noman’s supplied record shows 28 documents, 224 citations, and an h-index of 7, while his affiliation with Ningbo University places the research within an established academic institution. [1]

On the available evidence, the profile demonstrates measurable scholarly activity in quantum physics and quantum computing. The award assessment should nevertheless remain grounded in independently verifiable research outputs and the applicable criteria of the New Scientists Awards. Bibliometric measures can support an evaluation but should not be treated as a substitute for expert assessment of originality, methodological quality, significance, and sustained contribution.

Conclusion

Muhammad Noman’s academic profile is associated with Ningbo University, China, and the research area of quantum physics and quantum computing. The supplied bibliometric record reports 28 documents, 224 citations, and an h-index of 7. [1] These indicators, together with persistent researcher identifiers through ORCID and Google Scholar, provide a structured basis for documenting his scholarly profile. [2] [3]

In the context of the Research Excellence Award, the available information supports recognition of a research profile engaged with a technically significant and rapidly developing field.

References

  1. Elsevier. (n.d.). Scopus author details: Muhammad Noman, Author ID 59308497300. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=59308497300
  2. ORCID. (n.d.). Muhammad Noman — ORCID record. ORCID.
    https://orcid.org/0009-0003-6136-0114
  3. Google Scholar. (n.d.). Muhammad Noman — Google Scholar profile.
    https://scholar.google.com/citations?user=mUQqapYAAAAJ&hl=en
  4. New Scientists Awards. (n.d.). New Scientists Awards — Official Award Website.
    https://newscientists.net/
  5. Shor, P. W. (1994). Algorithms for Quantum Computation: Discrete Logarithms and Factoring. Proceedings of the 35th Annual Symposium on Foundations of Computer Science, 124–134. IEEE Computer Society Press. DOI: 10.1109/SFCS.1994.365700.
    https://doi.org/10.1109/SFCS.1994.365700

Yingbo Wu | Artificial Intelligence and Machine Learning | Innovative Research Award

Published on by New Scientists

Innovative Research Award

Yingbo Wu
Chongqing University, China

Yingbo Wu
Affiliation Chongqing University
Country China
Scopus ID 36976321800
Documents 65
Citations 905
h-index 16
Subject Area Artificial Intelligence and Machine Learning
Event New Scientists Awards
ORCID 0000-0002-6180-8762

Yingbo Wu is a researcher affiliated with Chongqing University, China, whose documented scholarly profile is associated with artificial intelligence and machine learning.These indicators provide a bibliometric view of research productivity and scholarly influence and are considered alongside the subject relevance and documented research contributions when assessing suitability for an innovative research recognition. [1]

Abstract

The Innovative Research Award recognition profile for Yingbo Wu highlights documented scholarly activity in artificial intelligence and machine learning.[1] The profile is situated within the broader development of computational methods that support intelligent systems, data-driven modelling, automated decision-making, and machine learning applications.

Keywords

Artificial intelligence; machine learning; intelligent systems; computational research; data-driven methods; algorithmic innovation; scholarly impact; research productivity; Chongqing University; Innovative Research Award.

Introduction

Artificial intelligence and machine learning have become important research areas across computer science, engineering, information systems, and interdisciplinary scientific applications. Research in these fields commonly addresses the development of computational models, learning algorithms, intelligent decision systems, pattern recognition approaches, and methods for extracting useful information from complex datasets. The scholarly record of an individual researcher can therefore be considered through both qualitative subject alignment and quantitative indicators of research activity.

Yingbo Wu is affiliated with Chongqing University in China and is identified in the supplied academic information with a research focus on artificial intelligence and machine learning. The Scopus author record supplied for this profile identifies 65 documents, 905 citations, and an h-index of 16. [1] These bibliometric measures provide a standardized basis for describing the scale and citation visibility of the documented research output.

Research Profile

Wu’s research profile is positioned within artificial intelligence and machine learning, a field characterized by the design and evaluation of computational systems capable of learning from data, recognizing patterns, supporting prediction, and performing tasks that traditionally require aspects of human reasoning. Within this broad discipline, research contributions may span theoretical models, algorithm development, system architecture, computational optimization, and application-oriented machine learning.

  • Affiliation: Chongqing University.
  • Primary subject area: Artificial Intelligence and Machine Learning.

Research Contributions

The supplied research classification places Wu’s scholarly activity within artificial intelligence and machine learning. This area encompasses research intended to improve the ability of computational systems to learn from structured or unstructured information and to perform analytical or predictive tasks. Such work can contribute to the broader development of intelligent computational methods and their application across scientific and engineering domains.

From an academic recognition perspective, the documented profile is relevant to innovation-oriented assessment because artificial intelligence and machine learning are strongly dependent on methodological development, computational experimentation, model evaluation, and the translation of research findings into practical or scientific applications. The available bibliometric record provides supporting evidence of continued scholarly dissemination and citation visibility. [1]

Publications

The supplied Scopus profile identifies 65 indexed documents associated with the researcher. [1] These indexed outputs form the bibliometric basis for evaluating publication activity in the context of this recognition profile. Because a complete publication list was not supplied as part of the source data, individual publication titles are not reproduced here to avoid attributing works without direct verification.

Publication indexing and citation data can provide useful evidence of scholarly dissemination. Scopus is a bibliographic and citation database widely used for tracking research publications and citation relationships, while DOI identifiers provide persistent links to individual scholarly works when available. [2] [5]

Research Impact

The supplied metrics indicate 905 citations across 65 documents and an h-index of 16. [1] In bibliometric terms, the h-index represents a threshold relationship between publication count and citation count, while total citations provide an aggregate measure of how frequently the indexed publications have been cited.

Within artificial intelligence and machine learning, research impact may be reflected through scholarly citations, methodological reuse, integration into subsequent studies, and application in computational or interdisciplinary settings. A balanced assessment therefore considers quantitative indicators together with the substance and relevance of the underlying research outputs.

Award Suitability

The available evidence supports consideration of Yingbo Wu for an Innovative Research Award within the New Scientists Awards framework. The principal documented factors are the researcher’s alignment with artificial intelligence and machine learning, an indexed publication record of 65 documents, 905 recorded citations, and an h-index of 16. [1]

Award suitability should be understood as an academic recognition assessment based on the available research record. The quantitative indicators establish a documented level of scholarly activity and citation visibility, while the subject-area alignment connects the profile with a rapidly developing field of scientific and technological research. Final recognition remains dependent on the applicable evaluation procedures of the New Scientists Awards.

Conclusion

Yingbo Wu’s documented academic profile at Chongqing University is associated with artificial intelligence and machine learning and includes 65 indexed documents, 905 citations, and an h-index of 16 according to the supplied Scopus information. [1] The combination of sustained publication activity, citation visibility, and relevance to a major contemporary research discipline provides a substantive basis for consideration within an innovative research recognition context.

The profile should be interpreted using the cited academic sources and current author records, with bibliometric indicators serving as supporting evidence rather than as a substitute for detailed peer evaluation of individual research contributions.

References

  1. Elsevier. (n.d.). Scopus author details: Yingbo Wu, Author ID 36976321800. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=36976321800
  2. Elsevier. (n.d.). Scopus: Abstract and citation database. Elsevier.
    https://www.scopus.com/
  3. ORCID. (n.d.). Yingbo Wu — ORCID record. ORCID.
    https://orcid.org/0000-0002-6180-8762
  4. New Scientists Awards. (n.d.). New Scientists Awards — Official Website.
    https://newscientists.net/
  5. Crossref. (n.d.). DOI Handbook and DOI metadata services. Crossref.
    https://doi.org/