Research
Applied research work related to AI and Data Science in enterprise systems.
Scalable Analytics for Enterprise Decisions: From MapReduce to Holiday-Aware Demand Forecasting
PublishedFive-stage data-to-decision workflow bridging MapReduce/Spark infrastructure with feature-first predictive modeling — tree-ensemble models for tabular enterprise data, two case studies.
Relevance: Directly maps to my enterprise data engineering work: pipeline scale, feature engineering discipline, and tree-ensemble modeling for business decision support align with the financial systems and AI governance focus of my doctoral research.
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Securing Connected Systems: A Layered Security Framework for WSNs, IoT/CPS, and Virtualized Networks
PublishedUnified security framework across wireless sensor networks, IoT/CPS, and virtualized infrastructure — common threat taxonomy, cryptographic defense analysis, and three implementation case studies.
Relevance: Bridges my enterprise systems background with doctoral research: threat modeling across layered architectures, post-quantum cryptography, and security engineering for distributed infrastructure.
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