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PranavShukla2/README.md

Pranav Shukla

What I do

Portfolio LinkedIn Blog Email Resume

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Hi, I'm Pranav πŸ‘‹

I ship across applied ML and full-stack SaaS β€” from healthcare biosignals to multi-tenant analytics in production. My work spans two worlds: one day it's a CNN reading single-lead physiological data, the next it's per-tenant isolation in an analytics SaaS. The throughline is the same β€” turn a hard, real-world problem into a working system people rely on.

  • πŸ”­ Currently building β†’ ArbFlow, a multi-tenant GA4 analytics SaaS running in production
  • πŸ«€ Researching β†’ sleep-apnea detection from single-lead signals (paper in progress)
  • 🌱 Gravitate toward β†’ early-stage teams where shipping is the job
  • πŸ’¬ Open to β†’ SWE internships Β· 2026 Β· remote-friendly
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πŸš€ Selected work

Project What it is
ArbFlow 🟒 Live Multi-tenant GA4 analytics SaaS β€” secure per-tenant data isolation and a clean product-metrics dashboard. Deployed and running in production. Β· Next.js FastAPI PostgreSQL Vercel
Sleep Apnea Detection Research Β· in progress 1D CNN detecting apnea from single-lead signals, validated with leave-one-patient-out CV. Accuracy is the wrong yardstick when events are rare β€” a model scores ~91% by mostly predicting normal and misses what matters. Rebuilding the evaluation around recall & PR-AUC over the apnea class is the core of the paper. Β· PyTorch 1D CNN LOPO CV SHAP
Self-Healing MLOps Pipeline Automated training pipeline that catches data drift statistically and retrains/rolls back before degradation reaches users β€” making reliability a property of the system instead of a fire drill. Β· Python Docker CI/CD
[Pre-Eclampsia Risk Model] Flags high-risk pregnancies early from routine clinical features β€” surfacing the signal that sits in checkup data before it becomes an emergency. Β· scikit-learn Pandas
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πŸ› οΈ Stack

Languages

Python TypeScript JavaScript Java C++ SQL

Frontend

Next.js React Tailwind Framer Motion

Backend & Data

FastAPI PostgreSQL REST APIs Power BI

ML / Ops

PyTorch scikit-learn Docker CI/CD

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πŸ“Š The stats

GitHub streak

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🧭 How I think about building

No grand process β€” just a loop I trust:

1. Find what actually matters β†’ 2. Ship the smallest thing that actually works β†’ 3. Put it in front of real users, fast β†’ 4. Measure β†’ fix β†’ repeat

So far, so good.

∿ ∿ ∿

🏏 Off the keyboard

I like a clean straight six. Same way I like shipping β€” line it up, make clean contact, send it.

Let's build something. Β· Email me Β· Portfolio Β· Resume

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