Computer Engineering student building ML and full-stack systems across healthcare, fintech, and open source.

• 🔬 Currently: Executive Certification in FinTech & AI (BITS School of Management × Masai) — capstone work in fraud detection & credit risk modeling
• 🛠️ Recent ML/full-stack work: clinical image synthesis, financial risk scoring, and spend analytics
• 🌱 Contributing to AegisAI (AI Governance, Risk & Compliance platform) via GSSoC 2026
• 📫 Reach me: LinkedIn · nehagirish31@gmail.com

MedSynth-AI AI-powered clinical image validation system — cGAN-based synthesis (PyTorch) with a Flask API backend and a React/TypeScript dashboard for clinicians to review outputs. Improved SSIM from 0.23 to 0.92 during training.

Sub-Zero Financial risk-monitoring tool integrating the RBI Account Aggregator framework, with a custom "Zombie Risk Score" algorithm to flag dormant/at-risk accounts. Flask + SQLite backend. Live demo

UPI Spend Intelligence Dashboard Streamlit dashboard analyzing UPI transaction patterns with K-Means customer segmentation. Live demo

bfhl-api Spring Boot REST API (Java 17, Maven) built and deployed live during a campus recruitment drive — containerized with Docker, deployed on Render.

AegisAI(fork, active contribution) Contributing an email notification system (FastAPI) as part of GSSoC 2026 — issue #966.

PythonJavaC++TypeScriptPyTorchFlaskReactSQLPower BIDocker