Title: TensorFlow-Driven NLP Conversational Agent
Role: AI Developer
Description: Developed a conversational AI agent leveraging TensorFlow's Natural Language Processing capabilities. The model is trained to parse user intent, handle context-aware dialogue, and deliver immediate responses. Designed to drastically reduce human latency in customer interaction pipelines and automate frontline support matrices.
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Title: Automated Data Routing & Classification Pipeline
Role: Machine Learning Engineer
Description: Engineered an automated machine learning architecture designed to eliminate manual data entry and optimize server storage. The system analyzes incoming file structures and intelligently classifies and routes them to their designated environment. This acts as a scalable proof-of-concept for enterprise-level document management and data sanitization.
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Engineered a context-aware, AI-powered discovery engine designed to solve the pedagogical disconnect in research and learning. The system acts as a high-performance orchestration layer, seamlessly merging localized datasets with global data providers (OpenAlex, Google Books) to curate resources specifically tailored to a user's comprehension level.
Architecture & Logic:
Backend: Built a decoupled REST API orchestration layer using ASP.NET (http://ASP.NET) Core.
AI Engine: Integrated ML.NET (http://ML.NET) (matrix factorization) for predictive multiclass classification.
Algorithm: Designed a custom Contextual Re-Ranking formula weighing semantic similarity against user demographics.
Infrastructure: Fully automated CI/CD pipeline deployed to Microsoft Azure (Linux Containers).