About Me
Computer Science undergraduate with hands-on experience in full-stack development, data science, and machine learning. Builds secure, scalable applications using Python, JavaScript, React, FastAPI, and Docker. Projects i…
Computer Science undergraduate with hands-on experience in full-stack development, data science, and machine learning. Builds secure, scalable applications using Python, JavaScript, React, FastAPI, and Docker. Projects include a self-verifying multi-agent RAG pipeline in LangGraph, a MERN-based Personalized Financial Assistant with JWT authentication and role-based access, and a document-processing app with OCR and NER-based data masking. AWS Certified Solutions Architect and Developer – Associate. Second Prize, SRM Intercollege Product Expo, for an IoT-based EV Monitoring System.
Experience
AI-ML Virtual Intern
<p>Completed a 10-week AI/ML internship covering data preprocessing, model development, and evaluation with Python.</p><p> Applied machine learning algorithms to real-world datasets through guided, project-based work.</p>
PROJECTS
Reliable AI Knowledge Layer
<p>• Built a self-correcting multi-agent RAG pipeline in LangGraph (routing, per-chunk relevance grading, query rewriting, web-search fallback, claim-level hallucination grading) for an HR/procurement policy assistant. • Designed a conflict and authority resolution step that uses version, effective-date, and “supersedes” metadata, returning a deterministic status (VERIFIED / CONFLICTING / INSUFFICIENT EVIDENCE) instead of guessing. • Built an ablation framework comparing 5 pipeline variants with RAGAS faithfulness scoring; supports pluggable Groq, OpenAI, Anthropic, and Gemini backends with structured JSON outputs. </p>