Hello, I'm

Rajat Patra

Machine Learning Engineer

Building AI-powered systems and seamless web platforms has always felt less like a job and more like a craft to me. The kind where you are never really done learning, and somehow that never gets old.

Lately that's Envault, a zero-knowledge secrets vault that's live in production, and a fantasy cricket XI predictor that won FIFS Gameathon 2.0 against 40+ Tier-1 teams. I obsess over the details most people never notice but always feel; that's just how I work.

Based in Bhubaneswar, India. You can reach me by email, or find me at @rajatpatra_.

Connect

Connect

If something you are building deserves that kind of attention, it would be great to connect. You can find me on any of the platforms below or reach out directly via email. Let's build something great.

Github Heatmap

One of the few things that shows my consistency.

Global Footprints

Community Impact.

Where I've Worked

I showed up, I learned, I delivered.

  • GDG on Campus ITER

    Bhubaneshwar, Odisha, India

    Core Member

    Part-Time

    AnchorEvent Management
  • Ekaayam

    Bhubaneshwar, Odisha, India

    Design Lead & Freelance Developer

    Freelance

    Node.jsReactFlaskFirebaseRazorpay
  • Virtual Showreel

    Bhubaneshwar, Odisha, India

    Lead Editor

    Full-Time

    Video EditingContent Creation

    Video Editor

    Full-Time

    Video EditingInstagram Shorts

Tech Stack

Tools I reach for without thinking twice.

What I've Built

Things I actually built and shipped.

AES-256-GCM envelope encryption over a master/data key hierarchy with automatic rotation.

Redis-cached decryption, Supabase RLS, and immutable audit logs.

Sync CLI that blocks git-tracked files and provisions JIT GitHub access.

Next.js · Supabase · Redis · Tailwind

Drafts an optimal IPL fantasy XI inside the 100-credit cap and squad rules.

Gradient-boosted regressor for player output, PuLP for the constraint solve.

Trained on ball-by-ball data from Cricsheet, Kaggle and ESPNcricinfo.

Python · XGBoost · PuLP · Docker

AI Generated Image Classification

Tells real photographs from AI-generated ones.

ViT-B/16 fine-tuned on CIFAKE — 100k+ images, 98.2% F1 on the standard test set.

Held its accuracy against adversarial examples.

CUDA-accelerated training cut run time by 85%.

PyTorch · Torchvision · scikit-learn

Brain Tumor Detection

A model comparison study for flagging tumors in MRI scans.

CNNs, DenseNet, VGG16 and vision transformers compared at ~90% average accuracy.

Hyperparameter tuning and augmentation run across every architecture.

Scored on confusion matrices, F1, recall, precision and AUC-ROC.

Keras · TensorFlow · scikit-learn

HealSync

Tracks hospital facility availability in real time over RFID.

Interface designed in Figma and Photoshop, then built out in Android Studio.

Python RFID reader publishing live facility status.

Google Maps API to surface the nearest hospitals to a user.

Python · Figma · Android Studio