Explainable AI in Medical Diagnostics
An applied research project evaluating how Grad-CAM, LIME, and SHAP improve interpretability for CNN-based chest X-ray diagnostics, with an emphasis on trust, clinical usability, and safe deployment.
Managing the Unmanageable: Multimodal AI for Unstructured Data Management and Analysis
A published research paper exploring multimodal AI systems for extracting structured insights from unstructured data, combining large multimodal models, retrieval-augmented generation (RAG), and agentic workflows. Focused on improving data understanding, system evaluation, and decision-making in complex environments.
Toward Sustainable Artificial Intelligence
An analysis of global data center sustainability patterns using country-level indicators to explore renewable adoption, energy usage, and the broader infrastructure footprint that supports modern AI systems.
Stability and Fairness in Strategic Systems: Nash Equilibrium and the Shapley Value
A deep dive into two foundational concepts in game theory, Nash equilibrium and the Shapley value, and how they jointly explain stability and fairness in strategic systems.
Game Theory: Foundations, Pioneers, and the Architecture of Strategic Systems
A comprehensive survey of game theory’s core principles, major contributors, and real-world applications, connecting foundational theory to business strategy, organizational design, sports, and machine learning systems.
Essay on the Future of Text Mining and Unstructured Data
A structured overview of text mining foundations and modern NLP developments, connecting traditional pipelines to transformer-era workflows and practical research tools, alongside ethical considerations.
Latent Semantic Analysis and Sentiment Analysis
A hands-on text mining project using latent semantic analysis (SVD/TF-IDF) to uncover themes in a large news corpus, combined with sentiment analysis to add interpretive context.