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.

 

Lili Chen | Environmental Science | Best Researcher Award

Dr. Lili Chen | Environmental Science | Best Researcher Award

Dr. Lili Chen, Chang’an University, China

Dr. Lili Chen, a Ph.D. candidate at Chang’an University, specializes in vegetation and climate change research. She earned her B.S. in geomatics engineering from Lanzhou University of Technology in 2022. Her research focuses on analyzing spatiotemporal vegetation changes in the northern foothills of the Qinling Mountains, incorporating climate time-lag effects and human activity assessments. Her study highlights the dominant influence of climate change on vegetation dynamics, providing insights for ecological restoration strategies. She has published in Environmental Research and aims to contribute to sustainable environmental management.

Profile

Google Scholar

Early Academic Pursuits 🎓

Lili Chen’s academic journey began with a strong foundation in geomatics engineering. She earned her Bachelor of Science (B.S.) degree from Lanzhou University of Technology in 2022, where she displayed exceptional analytical skills and a keen interest in environmental studies. Her undergraduate years were marked by rigorous coursework, hands-on research projects, and an unwavering passion for understanding the intricate relationship between the environment and technology. During this period, she developed a profound appreciation for the dynamic interplay between vegetation and climate, which would later become the cornerstone of her research.

Following her undergraduate studies, Lili Chen pursued a Ph.D. at Chang’an University, specializing in surveying and mapping. Her doctoral research is deeply focused on analyzing vegetation dynamics in response to climate change and human activities. Her early academic pursuits laid the groundwork for her innovative approach to assessing environmental sustainability.

Professional Endeavors 🌍

As a dedicated researcher at Chang’an University, Lili Chen has actively contributed to the scientific community through her meticulous study of vegetation changes. Her expertise lies in employing cutting-edge methodologies such as the Kernel Normalized Difference Vegetation Index (kNDVI) to assess ecological transformations. By integrating climate time-lag effects and human activity influences into her models, she provides a holistic perspective on environmental fluctuations.

Despite being at an early stage in her professional career, Lili has demonstrated an exceptional ability to translate theoretical concepts into practical insights. She has collaborated with faculty members, engaged in data-driven analysis, and participated in academic discussions aimed at shaping sustainable ecological policies. Her research has gained recognition for its methodological rigor and its potential to influence environmental conservation strategies.

Contributions and Research Focus 🌿

Lili Chen’s research primarily revolves around vegetation and climate change. Her notable project, “Spatiotemporal Changes of Vegetation in the Northern Foothills of the Qinling Mountains Based on kNDVI Considering Climate Time-Lag Effects and Human Activities,” is a groundbreaking study that spans over three decades (1986–2022). In this research, she meticulously examines the extent to which climate change and human interventions have impacted regional vegetation.

By incorporating advanced statistical models, multiple regression residuals methods, and remote sensing techniques, she has successfully quantified the relative influence of climate factors versus anthropogenic activities. Her findings indicate that climate change plays a more dominant role in shaping vegetation patterns than human-induced factors. This revelation is crucial for policymakers and environmentalists seeking effective strategies for ecological restoration.

Additionally, her work emphasizes the significance of time-lag effects in vegetation responses, offering new perspectives on long-term environmental planning. Her contributions extend beyond academia, as her research provides actionable insights for sustainable development, land use management, and biodiversity conservation.

Accolades and Recognition 🏆

Lili Chen’s scholarly contributions have earned her a nomination for the Best Researcher Award in the International Research Awards. Her research publication in Environmental Research, a prestigious SCI-indexed journal, underscores the scientific merit of her work.

Though early in her career, her dedication and intellectual rigor have been acknowledged by peers and mentors alike. Her research has also been cited in academic discussions on environmental sustainability, reinforcing her growing influence in the field of ecological studies. While she has not yet received patents or editorial appointments, her research trajectory suggests that such accomplishments are well within her reach.

Publication Top Notes

Highly transparent, underwater self-healing, and ionic conductive elastomer based on multivalent ion–dipole interactions

Author: Y Zhang, M Li, B Qin, L Chen, Y Liu, X Zhang, C Wang
Journal: Chemistry of Materials
Year: 2020

Superstretchable, yet stiff, fatigue-resistant ligament-like elastomers

Author: M Li, L Chen, Y Li, X Dai, Z Jin, Y Zhang, W Feng, LT Yan, Y Cao, C Wang
Journal: Nature Communications
Year: 2022

A highly robust amphibious soft robot with imperceptibility based on a water‐stable and self‐healing ionic conductor

Author: Z Cheng, W Feng, Y Zhang, L Sun, Y Liu, L Chen, C Wang
Journal: Advanced Materials
Year: 2023