Research & Writing
I enjoy writing research papers and technical articles that connect real-world engineering problems with practical AI, cloud, and data-driven solutions. My writing focuses on areas such as Generative AI platforms, AWS cloud architecture, data governance, Kubernetes-based AI systems, secure microservices, healthcare AI, and scalable engineering practices.
For me, writing is more than publishing papers. It is a way to explore ideas deeply, document engineering lessons, and share solutions that can help teams build reliable, secure, and scalable systems. I am especially passionate about research that bridges enterprise technology with emerging AI capabilities.
Published Papers
- Automating OpenSearch Snapshot Backup and Restore Using AWS Glue and Infrastructure as CodeJournal: IJRAI
- An Automated, Low-Cost AWS Cost Monitoring Framework for Daily Operational Anomaly DetectionJournal: IJEETR
- AetherStream: Predictive Rebalancing to Mitigate GPU Data Starvation in Kubernetes-Based AI SystemsJournal: JSEE
- Scalable Multi-Application CI/CD Pipeline Management using Master Pipeline ArchitectureJournal: IJRPETM
- Hardening the Wire: Real-Time Bytecode Shields as a Runtime Enforcement Layer for Zero-Trust MicroservicesJournal: LRJ
- A Secure and Governed Multi-Tenant Generative AI Platform Using Amazon Bedrock with Private API Gateway and Azure Entra ID IntegrationJournal: LRJ
- Zero Trust Architecture Using AWS IAM for Secure Data Lake Governance in Multi-Account AWS EnvironmentsJournal: LRJ
- AI-Driven Data Lineage Graphs Using Amazon DataZone, AWS Glue, and Lake Formation for Metadata-Driven GovernanceJournal: JSEE
- Efficient LLM Inference in Low-Resource Edge Systems: The Impact of Cold-Start, Warm-Start, and Memory ConstraintsJournal: LRJ
- Using Artificial Intelligence for Diabetes Healthcare: Synthetic Data Generation and Predictive Modeling for HIPAA-Compliant Clinical IntelligenceJournal: JSEE