11th grade · NES International School, Mumbai · building things that matter
I'm a high school developer who builds AI-driven projects that solve real problems, not demos that gather dust. Right now I'm most interested in algorithmic fairness, ML systems, and building tools that make complex ideas legible to anyone.
I learn by shipping. If something breaks, I want to know why it broke, not just how to patch it.
Fair Code — An open-source research project exposing and fixing bias in real-world AI systems. Audits four deployed algorithms — criminal justice (COMPAS), hiring, lending, and healthcare — using real datasets. Every experiment follows the same pipeline: train a biased model, measure the fairness gap, strip protected attributes and proxy variables, retrain, measure again. Up to 97.3% bias reduction achieved. Includes six deep-dive explainers on proxy variables, sampling bias, SHAP values, equalized odds, disparate impact, and why fairness metrics conflict.
Python · scikit-learn · pandas · SHAP · Fairlearn
↗ Live · ↗ GitHub · ⭐ 31 · 🍴 10
CardioAI — A cardiovascular risk predictor that turns clinical health parameters into an instant ML-based risk assessment. Users enter vitals like blood pressure, cholesterol, glucose, and BMI; the model outputs risk scores with an optional hypertension assessment module. Includes an AI assistant, interactive data visualisations, and a risk-reduction guide.
Python · ML · React · Next.js
↗ Live · ↗ GitHub · ⭐ 4
CareCompanion — A private health dashboard built for family caregivers. Manage medications, track vitals, log symptoms, prep for doctor visits, and chat with an AI that knows your patient's full history — all without a single byte of health data leaving your device. Tracks 31 lab readings across 8 groups, parses and auto-extracts data from medical PDFs, and includes an emergency info card accessible in one tap. Built for V1TROUS Hackathon 2026.
TypeScript · Next.js 14 · React · TailwindCSS · Groq AI
↗ Live · ↗ GitHub · ⭐ 3 · 🍴 1
Daily drivers: Python, JavaScript, React, HTML/CSS, Git
Have shipped with: scikit-learn, pandas, Next.js, TailwindCSS, Flask
Currently exploring: ML fairness, agentic AI systems, systems-level thinking, Rust
I don't build things to put them on a resume. I build them because the problem is interesting and the solution isn't obvious yet. I'm skeptical of hype — including my own — and I'd rather show measurable results than make claims.
Fair Code exists because I wanted to understand whether AI bias was actually fixable or just theoretically fixable. Turns out: it's fixable. The code is public. The numbers speak for themselves.
