About
4th-year B.Tech (CS — AI & ML) student with hands-on experience building AI/ML applications and full-stack systems. Developed production-grade RAG and computer-vision pipelines using LLMs, diffusion models, and modern web frameworks. Seeking a software engineering or ML internship to apply and grow these skills in a real-world environment.
Projects2
RAG System for Legal Question Answering · RAG Pipeline Developer
Built a Retrieval-Augmented Generation (RAG) pipeline using Qwen 3-4B, LangChain, and FAISS to answer queries on Indian constitutional articles, achieving retrieval accuracy of ~88% on a 500-article test set. Designed and integrated a full-stack app (React, Express.js, MongoDB) with sub-2-second average query response time. Implemented document chunking and embedding strategies that reduced irrelevant retrievals by ~30% vs. naive approach.
Open on github.com- Qwen 3-4B
- LangChain
- FAISS
- React
- Express.js
- MongoDB
Agri-LLaVA: AI-based Plant Disease Detection & Progression Prediction · CNN Developer
Trained a CNN classifier (Flask backend) to detect healthy vs. diseased leaves across 10 plant species, achieving 91% validation accuracy on a 3,000-image dataset. Integrated Stable Diffusion to generate visual projections of disease progression, enabling farmers to take preventive action 1–2 growth stages earlier. Built an interactive chatbot UI supporting real-time image uploads with diagnostic results returned in under 3 seconds.
Open on github.com- CNN
- Flask
- Stable Diffusion
Education3
B.Tech
2023 — 2027Keshav Memorial College of Engineering
Computer Science
Intermediate (PCM)
2021 — 2023Narayana Junior College
SSC
2019 — 2021Narayana Olympiad School
Certifications1
Developing AI Applications with IBM watsonx
2026IBM, issued via GeeksforGeeks