Best Researcher Award – Priyadarsini K
Priyadarsini K – SRM Institute of Science and Technology, India
Priyadarsini K is presented here in connection with the Best Researcher Award of Global Network Awards. Her documented scholarly work covers cloud computing, machine learning, Internet of Things analytics, embedded computing, and emerging wireless technologies. The article summarizes selected publications, researcher identifiers, and supplied bibliometric indicators using available public records. [1]
Abstract
Priyadarsini K is a researcher affiliated with SRM Institute of Science and Technology, India, whose documented work connects cloud computing, intelligent resource scheduling, machine learning, embedded systems, and Internet of Things data analytics. Her publications include studies of deep reinforcement learning for cloud Testing as a Service, classification of imbalanced time-series data, and IoT analytics with CNN accelerator architecture. A recent article examines graphene nanoribbon-based reconfigurable intelligent surfaces for terahertz 6G beam steering. The profile supplied for this recognition records 52 documents, 197 citations, and an h-index of 7 in Scopus; these metrics are presented as supplied, not independently verified. [4]
Keywords
Cloud computing, Testing as a Service, deep reinforcement learning, cloud resource scheduling, resource allocation, time-series classification, multi-class imbalanced learning, Internet of Things analytics, convolutional neural networks, CNN accelerator architecture, embedded systems, machine learning, and terahertz 6G communications. These terms reflect identifiable publication titles and documented research themes. [2]
Introduction
Priyadarsini K’s research profile brings together computational methods and connected technologies. Her publications address cloud-based testing, reinforcement-learning resource allocation, time-series classification, embedded-system design, and Internet of Things analytics. These themes reflect research across software systems, data-driven methods, and hardware-aware computing, with relevance to scalable digital services and intelligent applications research.
Research Profile
Priyadarsini K is associated with SRM Institute of Science and Technology in India. Institutional and scholarly profiles connect her work with computer science, cloud computing, data visualization, and machine learning. Her publications include IoT data analytics, CNN accelerator architecture, and research on terahertz intelligent surfaces for emerging wireless communications systems. [1]
Research Contributions
Priyadarsini K has co-authored work on deep reinforcement learning for resource scheduling in cloud Testing as a Service, addressing allocation decisions in variable environments. Other contributions examine multi-class imbalanced time-series classification and IoT data analytics with CNN accelerator architecture. Together, these studies connect algorithm design with practical computing systems applications. [2] [3]
Publications
Priyadarsini K’s publications include “Resource scheduling approach in cloud Testing as a Service using deep reinforcement learning algorithms” (2021) and “Towards Effective Time Series Classification of Multi-Class Imbalanced Learning” (2021). “IoT Data Analytics and CNN Accelerator Architecture” is listed. The 2026 paper studies graphene-nanoribbon surfaces for terahertz 6G beam steering. [2]
Research Impact
Priyadarsini K’s research addresses problems relevant to cloud service efficiency, data classification, connected-device analytics, and next-generation wireless systems. The supplied profile reports 52 documents, 197 citations, and an h-index of 7. These figures provide a quantitative snapshot, while publication quality, authorship contribution, and field context require separate assessment and comparison.[5]
Award Suitability
Priyadarsini K’s documented research themes provide a basis for consideration in a researcher-recognition programme focused on computing and connected technologies. Her work spans cloud resource scheduling, machine learning, time-series analysis, IoT analytics, and wireless-system design. Final award assessment should consider verified bibliographic records, individual contributions, research quality, and documented impact. [4]
Conclusion
Priyadarsini K’s publication record reflects interdisciplinary activity across cloud computing, machine learning, IoT analytics, embedded systems, and emerging wireless technologies. The cited studies demonstrate engagement with algorithmic questions and applied computing architectures. This profile summarizes available scholarly evidence and supplied metrics for recognition purposes, subject to verification against authoritative databases.[2]
External Links
References
- Karthik, P., & Sekhar, K. (2021). Resource scheduling approach in cloud Testing as a Service using deep reinforcement learning algorithms. CAAI Transactions on Intelligence Technology, 6(2), 147–154.https://doi.org/10.1049/cit2.12041
- Priyadarsini, K., Hemakesavulu, O., Karthik, S., & Karanam, S. R. (2021). Towards Effective Time Series Classification of Multi-Class Imbalanced Learning. Proceedings of the International Conference on Artificial Intelligence and Smart Systems, 1576–1582.
https://doi.org/10.1109/ICAIS50930.2021.9395778
- K. Priyadarsini, S. Karthik, Z. Hassan, & S. Praveen Kumar. (2026). Width-engineered graphene nanoribbon reconfigurable intelligent surfaces with an optimal quantum-confinement window for terahertz 6G beam steering: A computational study. Nanotechnology, 37(36).
https://doi.org/10.1088/1361-6528/aea29d
- ORCID. (n.d.). Priyadarsini K – ORCID researcher identifier. Persistent researcher identification and profile record.
https://orcid.org/0000-0003-2374-3184