Excellence in Research Award
Jeyaram G — Easwari Engineering College, India
Jeyaram G is a researcher affiliated with Easwari Engineering College whose work encompasses wireless sensor networks, cybersecurity, federated learning, blockchain, artificial intelligence, natural language processing, and intelligent network analysis. Recent publications address secure distributed learning, anomaly detection, semantic analytics, and lightweight intrusion detection, reflecting interdisciplinary engagement with contemporary technology and computing research. [1] [2] [3]
Abstract
Jeyaram G is a researcher affiliated with Easwari Engineering College whose work spans wireless sensor networks, cybersecurity, federated learning, blockchain, artificial intelligence, natural language processing, and intelligent network analysis. Recent publications examine privacy-preserving anomaly detection in industrial IoT, semantic-enhanced sentiment analysis of drug reviews, and lightweight real-time intrusion detection in dynamic vehicular networks. These studies demonstrate engagement with applied computational problems involving secure distributed learning, intelligent classification, and network protection. The publication portfolio provides a multidisciplinary basis for recognizing research activity in contemporary technology fields, particularly where artificial intelligence and secure networking intersect across practical engineering applications and data-driven systems. [1] [2] [3]
Keywords
Wireless Sensor Networks; Cybersecurity; Federated Learning; Blockchain; Industrial Internet of Things; Artificial Intelligence; Natural Language Processing; Sentiment Analysis; Intrusion Detection; Vehicular Networks.
Introduction
Jeyaram G is affiliated with Easwari Engineering College, India, and works in wireless sensor networks and related intelligent networking applications. His recent publications address privacy-preserving federated learning, blockchain-enabled industrial IoT security, semantic sentiment analysis, and lightweight intrusion detection, demonstrating research activity across secure networks and artificial intelligence and computing research. [1] [2] [3]
Research Profile
Jeyaram G’s publication record reflects interdisciplinary work connecting wireless networking, cybersecurity, federated learning, blockchain, natural language processing, and artificial intelligence. His research addresses distributed security, anomaly detection, semantic analysis, and real-time network protection, with applications spanning industrial IoT, healthcare text analytics, and dynamic vehicular communication environments and intelligent systems research. [1] [2] [3]
Research Contributions
The documented research contributions include a blockchain-integrated privacy-preserving federated learning framework for industrial IoT anomaly detection, a semantic-enhanced aspect-based sentiment analysis framework for drug reviews, and a lightweight sequential AI intrusion detection framework for vehicular networks. Together, these studies examine privacy, intelligent classification, distributed security, real-time detection, and innovation. [1] [2] [3]
Publications
Jeyaram G is a co-author of recent studies published in IETE Journal of Research, Intelligence-Based Medicine, and Scientific Reports. The publications address industrial IoT anomaly detection, drug-review sentiment analysis, and vehicular-network intrusion detection, respectively. These works provide documented evidence of research engagement across security, AI, networking, and intelligent data analysis. [1] [2] [3]
Research Impact
The cited publications indicate research activity addressing practical challenges in secure distributed computing and intelligent network analysis. The industrial IoT study examines privacy-preserving anomaly detection, the drug-review study applies semantic and machine-learning methods to health text, and the vehicular-network study targets real-time intrusion detection under dynamic communication conditions and resilience. [1] [2] [3]
Award Suitability
The documented publication portfolio aligns with an Excellence in Research Award through its coverage of contemporary research themes including cybersecurity, federated learning, blockchain, artificial intelligence, natural language processing, and network security. The record demonstrates participation in peer-reviewed research addressing applied technical problems across multiple domains, while available bibliographic metrics provide context. [1] [2] [3]
Conclusion
Jeyaram G’s documented research spans secure networking, industrial IoT, artificial intelligence, natural language processing, and intrusion detection. His recent publications demonstrate engagement with privacy-preserving learning, semantic analytics, and lightweight security frameworks. Collectively, these works establish a multidisciplinary research profile relevant to contemporary technology and engineering challenges in contemporary practice. [1] [2] [3]
External Links
References
- Thenmozhi, T., Karthi, S., Jeyaram, G., & Bhavani, M. (2026). PPFL-IIoT: A Blockchain-Integrated Privacy-Preserving Federated Learning Framework for Anomaly Detection in Industrial Internet of Things. IETE Journal of Research.
https://doi.org/10.1080/03772063.2026.2706080
- Meena, R., Lavanya, P. M., Revathi, K. P., & Jeyaram, G. (2026). Semantic-enhanced aspect-based sentiment analysis (SEM-EABSA) for drug reviews. Intelligence-Based Medicine, 14, 100369.
https://doi.org/10.1016/j.ibmed.2026.100369
- Jeyaram, G., Vidhya, V., Dhanaraj, R. K., & Alabdultif, A. (2026). A Lightweight Sequential AI Framework for Real Time Intrusion Detection in Dynamic Vehicular Networks. Scientific Reports, 16, 5217.
https://doi.org/10.1038/s41598-026-36103-2