Md Mehedi Hasan | Cybersecurity and Cryptography | Research Excellence Award

Research Excellence Award

Md Mehedi Hasan — Charles Sturt University, Australia

Md Mehedi Hasan
AffiliationCharles Sturt University
CountryAustralia
Scopus ID59181536600
Documents17
Citations6
h-index2
Subject AreaCybersecurity and Cryptography
EventInternational Research Awards
ORCID0000-0002-2081-6125

Md Mehedi Hasan is a researcher affiliated with Charles Sturt University, Australia, recognized through the Research Excellence Award category of the International Research Awards. His academic work focuses on cybersecurity and cryptography, contributing to research activities in secure computing, information protection, and emerging digital security challenges. [1]

Abstract

The Research Excellence Award recognizes scholarly contributions demonstrating research capability, innovation, and academic development within specialized fields. Md Mehedi Hasan’s research profile reflects engagement with cybersecurity and cryptography, areas central to protecting digital systems and advancing secure information technologies. [1]

Keywords

Cybersecurity, Cryptography, Information Security, Secure Computing, Digital Protection.

Introduction

Cybersecurity and cryptography represent essential research domains addressing confidentiality, authentication, privacy, and resilience of modern digital infrastructures. Researchers in these areas investigate methods to improve security frameworks and develop reliable solutions for evolving cyber threats. [2]

Research Profile

Md Mehedi Hasan is associated with Charles Sturt University, Australia. His indexed research record includes 17 documents, 6 citations, and an h-index of 2 according to available academic indexing information. [1]

Research Contributions

The researcher’s academic interests are connected with cybersecurity and cryptography, including the development and evaluation of approaches for improving security, privacy, and reliability in computational environments. [2]

Publications

Academic publications associated with cybersecurity research contribute to broader understanding of secure systems, cryptographic methods, and approaches for addressing challenges in digital environments. Research outputs are typically evaluated through scholarly indexing databases and citation metrics. [1]

Research Impact

Research impact is assessed through multiple indicators including scholarly publications, citations, academic collaboration, and contributions to knowledge development. The available citation profile provides measurable evidence of academic visibility. [1]

Award Suitability

The Research Excellence Award nomination highlights academic engagement, research activity, and contributions within cybersecurity and cryptography. The recognition aligns with researchers developing knowledge and solutions in important technology-focused disciplines.

Conclusion

Md Mehedi Hasan’s research profile represents continued involvement in cybersecurity and cryptography research. Through academic publications and scholarly contributions, the researcher participates in advancing understanding of secure digital systems.

References

  1. Elsevier. (2026). Scopus author details: Md Mehedi Hasan, Author ID 59181536600. Scopus.https://www.scopus.com/authid/detail.uri?authorId=59181536600
  2. Elsevier. (2026). ORCID author details: Md Mehedi Hasan, Author ID 0000-0002-2081-6125. ORCID.https://orcid.org/0000-0002-2081-6125

Ramkumar Kalyanaraman | Computer Science | Outstanding Scientist Award

Prof. Dr. Ramkumar Kalyanaraman | Computer Science | Outstanding Scientist Award

Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology | India

Dr. K. Ramkumar is a distinguished academician, researcher, and innovator with over twenty-three years of rich teaching and research experience in the field of Engineering and Computer Science. He is presently serving as a Professor in the Department of Computer Science and Engineering at Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, Tamil Nadu, India. His illustrious academic journey is marked by consistent dedication to research, innovation, and academic excellence. He obtained his Doctor of Philosophy (Ph.D.) in Computer Science and Engineering from Manonmaniam Sundaranar University, Tirunelveli, in 2018, specializing in Security and Privacy in Cloud Computing, a domain of critical importance in the digital era. To further enhance his expertise and broaden his research perspectives, he pursued a Post-Doctoral Fellowship (PDF) at the Federal University of Ceará, Fortaleza, Brazil, in 2023, focusing on Artificial Intelligence and Biomedical Data Analytics. Throughout his career, Dr. Ramkumar has held several prestigious leadership positions in academia, contributing extensively to institutional growth and quality enhancement. He has served as Professor and Head of the Department (CSE) at Rajalakshmi Institute of Technology, Chennai, and earlier as Professor and Associate Dean (Engineering & Technology) at SRM University, Delhi-NCR, Sonepat, Haryana, where he also chaired the Board of Studies. His earlier academic affiliations include SRM Institute of Science and Technology (Vadapalani Campus, Chennai), Kings Engineering College, and Indira Institute of Engineering and Technology, where he also functioned as Director of Placements. His industry exposure includes working with global technology companies such as Satyam Computer Services Ltd. and LogicaCMG Pvt. Ltd. (now CGI), where he held roles as Associate Consultant, IT Consultant, and Project Leader, leading large technical teams across onshore and offshore environments. Dr. Ramkumar’s research interests encompass a broad spectrum of emerging technologies including Cloud Computing Security, Artificial Intelligence, Machine Learning, IoT Frameworks, Blockchain Systems, and Biomedical Data Analytics. His prolific research output includes numerous publications in SCI, Scopus, and Web of Science-indexed journals, with several articles published in reputed platforms such as Elsevier, Springer, Taylor & Francis, and IEEE. His recent works focus on AI-based diabetic risk prediction, intelligent human activity recognition for assistive technologies, quantum image encryption, and deep learning applications for medical imaging. According to his Google Scholar profile, Dr. Ramkumar has achieved over 1,327 citations, with an h-index of 18 and an i10-index of 24, reflecting the global impact and scholarly recognition of his research contributions. His academic influence extends beyond publications, as he has co-supervised several Post-Doctoral Fellows at the Singapore Institute of Technology, demonstrating his commitment to mentoring and nurturing emerging researchers. Dr. Ramkumar has also published and been granted multiple patents across domains such as wireless sensor networks, mobile ad hoc networks, IoT-based monitoring systems, AI-driven diagnostic tools, and environmental pollution control mechanisms, reflecting his strong inclination toward innovation-driven applied research. Dr. K. Ramkumar stands as a dynamic academic leader whose contributions bridge academia, research, and industry, exemplifying excellence in technological innovation, knowledge dissemination, and professional leadership. His remarkable blend of teaching expertise, research achievements, and administrative acumen continues to inspire students, scholars, and peers across the global academic and scientific community.

Profiles: Scopus | Google Scholar

Featured Publications

Ramkumar, K. (2022). A comparative analysis of methods of endmember selection for use in subpixel classification: A convex hull approach. Computational Intelligence and Neuroscience, 2022, Article ID 3770871

Ramkumar, K., Ananthi, N., Brabin, D. R. D., Goswami, P., Baskar, M., & Bhatia, K. K. (2021). Efficient routing mechanism for neighbour selection using fuzzy logic in wireless sensor network. Computers & Electrical Engineering, 94, 107365.

Banerjee, U., Chakrabortty, J., Rahaman, S. U., & Ramkumar, K. (2024). One-loop effective action up to dimension eight: Integrating out heavy scalar(s). The European Physical Journal Plus, 139(2), 1–29.

Chakrabortty, J., Rahaman, S. U., & Ramkumar, K. (2024). One-loop effective action up to dimension eight: Integrating out heavy fermion(s). Nuclear Physics B, 1000, 116488.

Ramkumar, K., Medeiros, E. P., Dong, A., de Albuquerque, V. H. C., Hassan, M. R., & Hassan, M. M. (2024). A novel deep learning framework based Swin transformer for dermal cancer cell classification. Engineering Applications of Artificial Intelligence, 133, 108097.

Banerjee, U., Chakrabortty, J., Rahaman, S. U., & Ramkumar, K. (2024). One-loop effective action up to any mass-dimension for non-degenerate scalars and fermions including light–heavy mixing. The European Physical Journal Plus, 139(2), 169.