A real-time clinical vitals dashboard built in React and TypeScript, displaying live patient metrics including heart rate, SpO₂, temperature, respiratory rate, and blood pressure. Hand-rolled SVG sparklines replace heavy charting libraries, keeping the bundle lean and rendering smooth under continuous updates. Severity-based alerting with ARIA accessibility, memoized rendering, and derived state keep the UI responsive at high tick rates. Built to demonstrate what production-grade clinical frontend engineering actually looks like.
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A production-grade gRPC microservice written in Go for real-time clinical data ingestion. Built with bounded concurrency and backpressure to handle high-throughput streams without memory overflow, context-aware cancellation so no worker ever hangs on a slow downstream call, and graceful shutdown that drains in-flight work before the process exits. Transport and domain logic are cleanly separated, fully unit-tested with the Go race detector.
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A production-oriented RAG pipeline combining dense vector search and keyword search fused with Reciprocal Rank Fusion, cross-encoder reranking, and grounded answer generation with enforced citations. Built on PostgreSQL with pgvector and Redis, deployed on AWS with Docker and FastAPI. Includes an evaluation harness measuring hit rate, MRR, faithfulness, and answer relevance so every tuning decision is defensible, not vibes-based.
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Built and launched an AI-powered interview preparation platform that provides real-time interview assistance, personalized answer generation, and interview coaching. Designed and developed the full SaaS product including frontend, backend, AI integrations, authentication, subscriptions, and cloud infrastructure.
Technologies: React, TypeScript, Node.js, Python, OpenAI, AWS, PostgreSQL, Redis