Martin Sagayam Kulandairaj
SRM TRP Engineering College
Global Scientist Day Awards is an academic recognition initiative associated with acknowledging researchers, scientific contributions, and innovation across disciplines. This profile presents the supplied bibliometric information for Martin Sagayam Kulandairaj, affiliated with SRM TRP Engineering College in Trichy, India, and identifies machine learning as the stated subject area. It summarizes research-related indicators, outlines the broader context of scholarly impact, and discusses potential award suitability without asserting an independently verified award outcome. Author identification, publication records, and citation indicators should be checked against the relevant scholarly databases before formal publication or use in an award evaluation.[1][2]
Abstract
This article presents an academic recognition profile for Martin Sagayam Kulandairaj of SRM TRP Engineering College, Trichy, India, with machine learning identified as the principal subject area. The supplied bibliometric indicators report 171 documents, 3,382 citations, and an h-index of 32 under Scopus author identification number 56938711400.
Keywords
Global Scientist Day Awards; Martin Sagayam Kulandairaj; machine learning; computational research; bibliometrics; scientific publications; citation analysis; h-index; scholarly impact; research recognition; Scopus; ORCID; engineering research; academic evaluation; India.
Introduction
Academic recognition initiatives provide a framework for highlighting research achievements, encouraging knowledge exchange, and increasing the visibility of scientific work. The Global Scientist Day Awards website presents the event’s institutional platform and related information for prospective participants and researchers.[4][1][2]
Research Profile
The supplied profile associates Martin Sagayam Kulandairaj with SRM TRP Engineering College in Trichy, India, and identifies machine learning as the relevant subject area. Machine learning is a branch of artificial intelligence concerned with computational methods that identify patterns in data and support prediction, classification, optimization, and related analytical tasks.[1][2]
Research Contributions
The specific research contributions of Martin Sagayam Kulandairaj should be established through examination of verified publications and their documented findings. Within machine learning, scholarly contributions may include methodological development, algorithm evaluation, model interpretability, data analysis, or applications in engineering and other scientific fields. [3]
Publications
The supplied profile reports 171 documents associated with Scopus author ID 56938711400. This figure should be treated as a reported database metric rather than an independently confirmed publication count. A publication review should establish which records are journal articles, conference papers, reviews, book chapters, or other document types and determine whether duplicate records or author-name ambiguities are present. [1]
Research Impact
The supplied bibliometric profile reports 3,382 citations and an h-index of 32. Citation counts indicate how frequently indexed documents have been cited within a database and its coverage period, while the h-index combines publication productivity and citation frequency according to a defined threshold. These indicators can help describe patterns of scholarly attention, but they are influenced by career duration, field-specific citation practices, database coverage, co-authorship, and document type. [1][3]
Award Suitability
The supplied research profile may be considered as a starting point for evaluating suitability for the Global Scientist Day Awards. The reported publication and citation indicators provide measurable information that an assessment panel could verify, while the stated machine learning subject area may help guide disciplinary review. [4]
Conclusion
This academic profile summarizes the supplied information for Martin Sagayam Kulandairaj, including the stated affiliation with SRM TRP Engineering College, Trichy, the machine learning subject area, and the reported Scopus indicators of 171 documents, 3,382 citations, and an h-index of 32. Scopus and ORCID provide useful starting points for checking the researcher’s identity and scholarly record.
External Links
References
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- Elsevier. (2026.). Scopus author details: Martin Sagayam Kulandairaj, Author ID 56938711400. Scopus.
https://www.scopus.com/authid/detail.uri?authorId=56938711400
- ORCID. (2026.). ORCID record: 0000-0003-2080-0497. ORCID.
https://orcid.org/0000-0003-2080-0497
- A Multilevel Deep Learning Model for Automated Brain Tumor Segmentation Using Magnetic Resonance Images.
https://www.mdpi.com/2075-4418/16/14/2259
- Global Scientist Day Awards. (2026.). Official event website.
https://scientistday.org/