Final-year Computer Science student at VIT Vellore, specializing in full-stack and backend development with hands-on experience building AI/ML systems. 3x IEEE research papers.
- Full-Stack Web Apps — MERN stack, REST APIs, cloud deployment
- AI/ML Systems — RAG pipelines, vector search, LLMs, speech processing
- Research — Battery health prediction, document QA systems, cryptographic schemes
| Paper | Status | Conference |
|---|---|---|
| Lightweight AI-Based Battery Health Prediction for EVs | Published IEEE Xplore | IEEE IDCIoT 2026 |
| Voice-Based RAG System for Document-Restricted QA | Submitted | IC-SIT 2026 |
| Lightweight Cryptographic Schemes for Body Sensor Networks | Accepted & Presented | TQCEBT'26 |
Languages: Java · JavaScript · Python · C/C++
Frontend: React.js · HTML · CSS · Bootstrap · Tailwind CSS
Backend: Node.js · Express.js · FastAPI
Databases: MongoDB Atlas · MySQL
AI/ML: PyTorch · FAISS · Sentence-Transformers · Whisper · Pandas
Tools: Git · Postman · AWS (EC2) · Render · Vercel
- Voice-Based RAG System — 86.6% accuracy, 3.3% hallucination rate
- WanderInn — Travel Listing Platform — Deployed on Render
- [TDAN — Battery Health Prediction] — R²=0.998, IEEE accepted
- FundCommunity — Non-Profit Platform — UPI donations, React