Gang Li | Agricultural Data Analysis | Best Researcher Award

Published on by Research Data Analysis

Best Researcher Award

Gang Li – Nanjing Agricultural University, China

Gang Li
Affiliation Nanjing Agricultural University
Country China
Scopus ID 56520660900
Documents 109
Citations 395
h-index 11
Subject Area Agricultural Data Analysis
Event International Research Data Analysis Excellence & Awards

Gang Li is a researcher affiliated with Nanjing Agricultural University, China, whose academic profile is associated with agricultural data analysis. The supplied Scopus record reports 109 documents, 395 citations, and an h-index of 11. This article summarizes the available profile information and its relevance to research recognition. [1]

Abstract

This article presents the available academic profile of Gang Li of Nanjing Agricultural University, China, in the context of agricultural data analysis. The supplied Scopus information lists 109 documents, 395 citations, and an h-index of 11. These indicators provide a bibliometric overview but do not independently establish research quality or award eligibility. [2]

Keywords

Gang Li; Best Researcher Award; Agricultural Data Analysis; Nanjing Agricultural University; Bibliometrics; Research Publications; Citation Analysis; Research Impact.

Introduction

Agricultural data analysis supports evidence-based research by examining agricultural observations, identifying patterns, and informing scientific interpretation. Gang Li, affiliated with Nanjing Agricultural University, is presented here in this research context. The available profile provides bibliometric indicators for reviewing scholarly activity, while detailed publications and research contributions require independent verification. [3]

Research Profile

Gang Li is affiliated with Nanjing Agricultural University in China. The supplied Scopus author record identifies the researcher through author ID 56520660900 and reports 109 documents, 395 citations, and an h-index of 11. These figures summarize the provided profile snapshot; publication-level details and current metrics should be checked against the indexed record. [2]

Research Contributions

Agricultural data analysis can contribute to research through data interpretation, statistical evaluation, and evidence-based assessment of agricultural systems. The supplied subject area associates Gang Li’s profile with this field. Specific methods, datasets, findings, and applications cannot be established from bibliometric indicators alone and should be described using verified publications and institutional research information. [1]

Publications

The supplied Scopus profile reports 109 documents associated with Gang Li. This document count offers a broad indication of indexed scholarly output but does not identify individual titles, publication dates, journals, or author roles. A complete publication overview should therefore be prepared from the verified author record and checked against each publication’s bibliographic details. [3]

Research Impact

The supplied bibliometric snapshot records 395 citations and an h-index of 11 for Gang Li. Citation counts reflect indexed citation activity, while the h-index combines publication and citation information. Both indicators depend on database coverage and timing; they should be interpreted alongside research quality, contribution details, disciplinary context, and the relevance of individual studies. [1]

Award Suitability

Gang Li’s supplied academic profile provides information relevant to consideration for the Best Researcher Award associated with the International Research Data Analysis Excellence & Awards. The reported publication and citation indicators may support an application review. Final suitability depends on the award’s published eligibility criteria, documented research contributions, supporting evidence, and the organizers’ assessment. [2]

Conclusion

The available profile identifies Gang Li as a researcher affiliated with Nanjing Agricultural University, China, and provides a bibliometric snapshot of scholarly activity. These details offer a starting point for academic recognition. A comprehensive evaluation should include verified publications, research contributions, methodological significance, and documented alignment with the award’s eligibility requirements. [3]

References

  1. Elsevier. (n.d.). Scopus author details: Gang Li, Author ID 56520660900. Scopus. Retrieved September 28, 2026, from
    https://www.scopus.com/authid/detail.uri?authorId=56520660900
  2. International Research Data Analysis Excellence & Awards. (n.d.). Research Data Analysis. Retrieved September 28, 2026, from
    https://researchdataanalysis.com/
  3. Laser Radar and Micro-Light Polarization Image Matching and Fusion Research.
    https://www.mdpi.com/2079-9292/14/15/3136

Ziliang Wu | Agricultural Data Analysis | Best Researcher Award

Published on by Research Data Analysis

Best Researcher Award

Ziliang Wu — South China Agricultural University, China

Ziliang Wu
Affiliation South China Agricultural University
Country China
Documents 1
Subject Area Agricultural Data Analysis
Event International Research Data Analysis Excellence & Awards
ORCID 0009-0006-5271-260X

Ziliang Wu is affiliated with South China Agricultural University, China, and is associated with the subject area of Agricultural Data Analysis. The available research record identifies one document and an ORCID researcher identifier, providing a limited but verifiable basis for academic recognition within the stated award context. [1]

Abstract

This academic recognition profile presents Ziliang Wu of South China Agricultural University in the context of the Best Researcher Award. The available information identifies Agricultural Data Analysis as the relevant subject area, with one documented research output and an ORCID identifier. The profile emphasizes evidence-based assessment while avoiding unsupported claims concerning citation performance, h-index, publication volume, or broader research influence. [2]

Keywords

Keywords: Agricultural Data Analysis; Research Data Analysis; Agricultural Research; Data-Driven Agriculture; Computational Agriculture; Research Evaluation; Scholarly Communication; South China Agricultural University; Best Researcher Award.

Introduction

Agricultural Data Analysis applies quantitative and computational approaches to agricultural information, supporting interpretation of complex datasets and research evidence. Ziliang Wu’s affiliation with South China Agricultural University places the profile within an agricultural research environment, while the available record provides a focused basis for documenting research activity and scholarly identification. [3]

Research Profile

Ziliang Wu is associated with South China Agricultural University in China and is identified in the subject area of Agricultural Data Analysis. The supplied record indicates one document and provides an ORCID identifier for researcher disambiguation. Additional bibliometric indicators, including citations and h-index, are not available in the supplied information. [2]

Research Contributions

The documented contribution is situated within Agricultural Data Analysis, a field concerned with organizing, interpreting, and evaluating agricultural research data. Because detailed publication titles, methodologies, findings, and datasets were not supplied, specific scientific contributions cannot be independently characterized. The available record supports recognition of research activity without extending beyond documented evidence. [1]

Publications

The available profile records one document associated with the researcher. No complete bibliographic information, publication title, journal details, publication year, or DOI has been provided in the available data. Consequently, the publication record should be interpreted conservatively until the underlying scholarly source is independently verified through an authoritative bibliographic database. [3]

Research Impact

Research impact is commonly assessed through evidence such as citations, scholarly outputs, collaboration, adoption, and practical or societal applications. For Ziliang Wu, the supplied record confirms one document but does not provide citation totals or an h-index. Therefore, a quantitative assessment of research impact cannot be established from the available evidence. [2]

Award Suitability

The profile demonstrates a documented connection to Agricultural Data Analysis and an academic affiliation with South China Agricultural University. These characteristics are relevant to a Best Researcher Award focused on research data analysis. However, final award suitability should consider verified publications, methodological contributions, research quality, citations, and broader impact where such evidence is available. [1]

Conclusion

Ziliang Wu’s available academic profile establishes an affiliation with South China Agricultural University and a subject-area association with Agricultural Data Analysis. One documented research output and an ORCID identifier provide foundational evidence for the recognition profile. More comprehensive assessment would require verified publication, citation, methodological, and impact information from authoritative sources. [3]

References

  1. A full-process closed-loop UAV inspection system for citrus disease detection in communication-constrained orchards based on SPN-YOLO.
    https://www.researchgate.net/publication/413759067_A_full-process_closed-loop_UAV_inspection_system_for_citrus_disease_detection_in_communication-constrained_orchards_based_on_SPN-YOLO
  2. ORCID. (n.d.). Ziliang Wu: ORCID record. ORCID.
    https://orcid.org/0009-0006-5271-260X
  3. South China Agricultural University. (n.d.). South China Agricultural University. Institutional information.
    https://www.scau.edu.cn/