I'm a B.Tech CS (Data Science) graduate from UPES and a Full Stack Developer.

My expertise lies at the intersection of Data Science and Application Development. Whether it's training machine learning models to predict clinical outcomes or building production-ready Android marketplaces, I love turning complex problems into elegant, user-centric solutions.

Previously, I built end-to-end ML pipelines as a Data Science Intern at IBM.

⚒️ Currently building: FlowForge, a card game where every card is a real PC automation.

🌱 Currently learning: Advanced Agentic AI & Azure Cloud Architecture.

A deckbuilder where every card is a real PC automation. Snap WHEN / IF / THEN cards into combos that sort downloads, watch web pages, back up files and ping Discord, then level them up by running them. Zero dependencies, hand-drawn SVG card art, and a test suite that runs on Windows, macOS and Linux.

Node.js Vanilla JS SVG GitHub Actions

An enterprise-grade Slack bot that answers team questions from internal documents using RAG, LangChain, and GPT-4o.

Python Pinecone LangChain OpenAI

Unifies candidate data from three recruitment sources, automates deduplication and LLM skill tagging with n8n, and ships an audio collection app with signal analysis.

FastAPI n8n SQLite NumPy / SciPy

A production-ready two-sided Android marketplace connecting taxpayers & CAs, featuring in-app WebRTC video consultations.

Kotlin MVVM WebRTC Firebase

Reproducible ML pipeline achieving 85%+ accuracy on clinical data. Corrected class imbalances using SMOTE.

Python Scikit-learn Pandas

Supervised classification model trained on a 10,000-record telecom dataset, achieving an impressive 91% AUC-ROC.

Python XGBoost Random Forest