Jay Novew

I designed and developed QRYPTA, a modern web application for encrypting, storing, and securely sharing sensitive documents using CSF post‑quantum cryptography. The platform replaces traditional RSA/AES schemes with future‑proof, quantum‑resistant encryption, ensuring long‑term data protection.

Key Responsibilities & Achievements

Built a full‑stack architecture using Next.js 14+ (TypeScript) and FastAPI (Python 3.11).

Implemented server‑side encryption with the csf-crypto library, ensuring files are never stored in plaintext.

Developed a complete key management system (generate, import, export).

Integrated Supabase for authentication (email + OTP), PostgreSQL database, and secure storage.

Created a secure file‑sharing workflow with password protection and expiration controls.

Built a dashboard with activity logs, alerts, statistics, and performance benchmarks comparing CSF vs RSA.

Deployed the platform using Vercel (frontend) and Render (backend), with automated setup scripts.

Tech Stack

Frontend: Next.js, TypeScript, Tailwind CSS

Backend: FastAPI, Python

Database & Storage: Supabase PostgreSQL + Supabase Storage

Auth: Supabase Auth (email + OTP)

Cryptography: CSF post‑quantum encryption (Kyber‑based)

DevOps: Vercel, Render, Bash automation

Impact

QRYPTA delivers a quantum‑secure document vault where encryption happens before storage, keys remain under user control, and sharing is fully protected. The system provides a reliable, modern alternative to legacy encryption methods for individuals and organizations needing long‑term data security.

I completed the core curriculum at École 42 Lausanne, a highly selective, project‑based software engineering program known for its intensive, peer‑learning methodology and real‑world technical challenges.

Key Achievements & Skills

Mastered low‑level programming through C language, memory management, pointers, and algorithmic problem‑solving.

Built multiple system‑level projects including custom libraries, shell implementations, and algorithmic challenges.

Developed strong skills in Unix systems, Bash scripting, Git workflows, and collaborative development.

Learned to work autonomously, debug complex issues, and deliver clean, maintainable code under pressure.

Completed team projects requiring communication, leadership, and agile problem‑solving.

Impact

At Helitek, I worked on automation, embedded systems, and AI‑powered computer vision solutions designed for industrial and aeronautical environments. My role focused on developing intelligent algorithms, optimizing embedded hardware workflows, and building reliable automation pipelines capable of running in constrained, real‑time conditions.

Key Responsibilities & Achievements

Designed and implemented computer vision algorithms for object detection, tracking, and real‑time analysis on embedded hardware.

Developed automation systems integrating sensors, microcontrollers, and custom logic to improve operational efficiency and reduce manual workload.

Built and optimized embedded software running on low‑power devices, ensuring stability, performance, and fault‑tolerance.

Created AI‑driven modules for pattern recognition, anomaly detection, and decision‑making in autonomous workflows.

Collaborated on system architecture involving data acquisition, preprocessing, model inference, and hardware‑level integration.

Improved reliability and throughput of existing pipelines through algorithmic optimization and hardware‑aware engineering.

Tech Stack & Tools

Embedded C / C++

Python (AI, automation, CV pipelines)

OpenCV, TensorFlow / PyTorch (vision & inference)

Microcontrollers, sensors, and hardware interfaces

Real‑time systems, low‑level debugging, performance tuning