Amal Krishna Mitra |Health Sciences | Best Researcher Award

Best Researcher Award

Amal Krishna Mitra
Texas Tech University Health Sciences Center

Amal Krishna Mitra
Affiliation Texas Tech University Health Sciences Center
Country United States
Scopus ID 7402543246
Documents 114
Citations 3,614
h-index 27
Subject area Medicine and Health Sciences
Event International PopularScientist Awards
ORCID 0000-0003-4238-7322

Amal Krishna Mitra is presented in this article as a candidate for the Best Researcher Award associated with the International PopularScientist Awards. The profile records an institutional affiliation with Texas Tech University Health Sciences Center in the United States. These bibliometric indicators provide a quantitative starting point for examining scholarly output and citation impact, although they should be interpreted alongside publication-level verification, research quality and the candidate’s specific contributions. [1] [2]

Abstract

This article presents a structured academic recognition profile for Amal Krishna Mitra in connection with the Best Researcher Award at the International PopularScientist Awards. The supplied profile data identify Texas Tech University Health Sciences Center as the institutional affiliation and Medicine and Health Sciences as the subject area. Reported bibliometric indicators include 114 documents, 3,614 citations and an h-index of 27, associated with Scopus author identifier 7402543246. An ORCID identifier is also supplied for researcher identification. [1] [2]

Keywords

Amal Krishna Mitra; Best Researcher Award; International PopularScientist Awards; research evaluation; bibliometric analysis; Scopus author profile; citation impact; h-index; Medicine and Health Sciences; academic research; scholarly publications; research integrity; ORCID.

Introduction

Researcher recognition commonly considers the quantity and influence of scholarly publications, the originality of research findings, methodological quality, collaboration and relevance to a field. Bibliometric indicators can help summarize publication and citation patterns, but they do not independently measure scientific rigor, reproducibility, societal benefit or an individual’s contribution to collaborative research. Interpretation should therefore combine quantitative information with qualitative assessment and careful verification of the underlying records. [3] [4]

Research Profile

The profile information supplied for Amal Krishna Mitra identifies Texas Tech University Health Sciences Center as the institutional affiliation and the United States as the country. The stated research subject area is Medicine and Health Sciences. The supplied Scopus identifier is 7402543246, while the ORCID iD is 0000-0003-4238-7322. These identifiers provide starting points for checking identity and publication attribution in authoritative researcher databases. [1] [2]

Research Contributions

An evidence-based account of research contributions should identify the questions investigated, the methods used, the candidate’s role in collaborative projects and the outcomes supported by published evidence. Relevant documentation may include original research articles, review papers, clinical or laboratory studies, methodological developments, datasets, patents and documented translational applications. Each item should be matched to a reliable author record before being used to support an award assessment.

Publications

A publication list is central to evaluating academic activity, but accurate attribution is essential. The five bibliographic records supplied with the request are listed below as source-provided records for verification only. They should not be interpreted as confirmed publications by Amal Krishna Mitra. Where a DOI was provided, the identifier links to the corresponding DOI resolver; the absence of a DOI in the supplied excerpt is indicated without speculation.

  1. Hydrogel tissue expanders for stomatology. Part I. Methacrylate-based polymers. Journal of Materials Science: Materials in Medicine (2017). The supplied record lists Hrib, J.; Sirc, J.; Lesny, P.; Hobzova, R.; Duskova-Smrckova, M.; Michalek, J.; and Smucler, R.
  2. Infantile hemangiomas. Current treatment procedures | Infantilní hemangiomas. Současné léčebné prostředky. Czech-Slovak Pediatrics (2017). The supplied record lists Malis, J.; Stara, V.; Blahova, K.; Bučkova, H.; Faberova, R.; Šterba, J.; Klovrzova, S.; Kynčl, M.; Černy, M.; Hrdlička, R.; and additional contributors. Scopus EID: 2-s2.0-85027991512. No DOI was supplied in the excerpt. The record is not verified as belonging to the candidate.
  3. Direct and indirect treatment of pain with lasers – Update 2016. Disease (2016), as recorded in the supplied bibliographic excerpt. The listed contributors are Šmucler, R. and Jenčová, J. Scopus EID: 2-s2.0-84992323214. No DOI was supplied in the excerpt. The journal metadata and authorship should be checked against the original record.

Research Impact

The supplied profile reports 114 documents, 3,614 citations and an h-index of 27. These values can be used as provisional bibliometric indicators for the profile, subject to confirmation against the relevant database at the time of assessment. Citation counts vary across databases, update cycles, document types and author-disambiguation procedures. They should therefore be reported with a source and retrieval date in formal award documentation. [1]

Award Suitability

The Best Researcher Award profile is intended to support a transparent review of scholarly activity within Medicine and Health Sciences. The reported bibliometric indicators may be relevant to an initial screening process, but the information available here is not sufficient to establish final eligibility, confirm individual authorship across the supplied records or determine an award outcome. Assessment should follow the award organizer’s published eligibility rules and evaluation criteria.

Conclusion

This article provides a structured academic recognition profile for Amal Krishna Mitra in relation to the Best Researcher Award at the International PopularScientist Awards. The supplied information reports an affiliation with Texas Tech University Health Sciences Center, a subject area of Medicine and Health Sciences, 114 documents, 3,614 citations and an h-index of 27. These figures are presented as provided and require current database verification. The publication excerpts accompanying the request do not establish authorship by the named candidate and have therefore been explicitly separated from a verified bibliography.

References

  1. Elsevier. (n.d.). Scopus author details: Amal Krishna Mitra, Author ID 7402543246. Scopus. Profile identifier and bibliometric values are supplied in the article input and have not been independently verified in a live database retrieval.
    https://www.scopus.com/authid/detail.uri?authorId=7402543246
  2. ORCID. (n.d.). ORCID record identifier 0000-0003-4238-7322. ORCID. The identifier was supplied in the article input; identity and record details should be checked against the live profile.
    https://orcid.org/0000-0003-4238-7322
  3. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences, 102(46), 10.1073/pnas.0507655102.
  4. San Francisco Declaration on Research Assessment (DORA). (2012). San Francisco Declaration on Research Assessment. Guidance on responsible research assessment and the limitations of journal-based metrics.
    https://sfdora.org/read/
  5. International PopularScientist Awards. (n.d.). Award information and official website. Eligibility requirements, assessment procedures and event details should be confirmed using the organizer’s current official information.
    https://popularscientist.com/

Yashbir Singh | Medicine and Health Sciences | Best Researcher Award

Dr. Yashbir Singh | Medicine and Health Sciences | Best Researcher Award

Assistant Prof Mayo clinic, Rochester United States

Yashbir Singh is an Assistant Professor in Radiology with extensive experience in biomedical engineering and computational deep learning methods for medical imaging analysis. His research focuses on AI-driven approaches for early cancer detection, particularly in liver cancer, and has made substantial contributions to the integration of topological data analysis with deep learning. With a background in pharmaceutics, bioinformatics, and biomedical engineering, Yashbir brings a unique interdisciplinary perspective to medical imaging. His work is instrumental in advancing AI methodologies for clinical applications and patient-specific risk assessments in liver diseases. 🌐💡

Profile

Google Scholar

Orcid

Education

Yashbir Singh completed his Bachelor’s in Pharmaceutics and Drug Design from M.J.P. Rohilkhand University, Bareilly, India, followed by a Master’s in Bioinformatics from the Indian Institute of Information Technology, Allahabad. He then earned his PhD in Biomedical Engineering from Chung Yuan Christian University, Taiwan. After completing his postdoctoral work in AI Radiology at Mayo Clinic, he continued his research at the same institution as a Postdoctoral Fellow in AI Radiology. 🎓🔬

Experience

Yashbir Singh has held various prestigious positions, including visiting faculty at Harvard Medical School and a medical scientist at WVU Medicine, West Virginia. He has also been a junior research fellow at IIT Mandi, India, and a teaching assistant at IIIT Allahabad, India, and Chung Yuan Christian University, Taiwan. His diverse experiences across academia and clinical environments have significantly shaped his research in medical imaging and AI. 🌍👨‍⚕️

Research Interest

Dr. Singh’s research interests lie in the intersection of artificial intelligence, medical imaging, and oncology. He has pioneered the use of algebraic topology-based machine learning for predicting clinical outcomes, specifically in liver diseases like primary sclerosing cholangitis. His current work focuses on developing deep learning frameworks for early cancer detection, integrating machine learning with topological data analysis, and improving patient-specific diagnostic tools. 🔍💻🧬

Award

Yashbir Singh has received several prestigious awards, including the 2024 Research Award from RSNA and Best Paper Presenter at IEEE CCWC 2022. His work has been recognized for its innovation in AI-driven medical imaging and clinical applications. In addition, he has received Best Reviewer Awards from ICSPIS and the 2020 Medical Imaging Best Paper Award from SPIE. These accolades highlight his leadership in the field of AI-based medical research. 🏆📜

Publication Top Notes:

Yashbir Singh has contributed to over 20 high-impact publications. Some notable works include:

Decoding ChatGPT: a taxonomy of existing research, current challenges, and possible future directions

Mitigating bias in radiology machine learning: 1. Data handling

Mitigating bias in radiology machine learning: 2. Model development

The future of gpt: A taxonomy of existing chatgpt research, current challenges, and possible future directions

A low-cost texture-based pipeline for predicting myocardial tissue remodeling and fibrosis using cardiac ultrasound

Identification of Novel Abiotic Stress Proteins in Triticum aestivum Through Functional Annotation of Hypothetical Proteins

Algebraic topology-based machine learning using MRI predicts outcomes in primary sclerosing cholangitis

His work is highly cited, demonstrating a significant impact on the field of AI and medical imaging, especially in the context of liver disease. 📖📈