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Computer Science Graduate  ·  Full-Stack Engineer  ·  AI Builder

Building intelligent
products that scale.

I design and build production-ready AI systems, full-stack applications, and scalable software — from research to real-world deployment.

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[ NEURAL ARCHITECTURE ]

[ AUTONOMOUS SYSTEMS ]

UNIT

AI AGENT

STATUS

ONLINE

Systems built
to solve
real problems

AI / MLCompleted
01

SentinelAI

Hybrid Edge–Cloud Violence Detection Architecture

PythonMobileNetV2OpenAI Vision APIComputer Vision+4
Backend
02

LendGraph

Private credit infrastructure for automated loan management and investor intelligence

KotlinSpring BootPostgreSQLReact+3
Backend
03

Fitness Tracking API

Production-grade REST API with RBAC, HATEOAS, and ETag caching

Node.jsKoaMySQLJWT+3
AI / ML
04

RegulaPilot

AI-powered compliance workflow system with a real backend and structured LLM pipeline

ReactNext.jsTypeScriptTailwind+5
05

Café Digital Growth & Operations Platform

End-to-end system for customer engagement, retention, and business operations

ReactNode.jsExpress/KoaMySQL+3
System Design

Explore the Architecture

Step inside the systems behind my projects — from user action to backend response.

Click any node to explore its role in the system

RESTful API with JWT authentication, RBAC middleware, and a layered backend architecture built on Koa.js and MySQL.

Client

Vue SPA Client

Single-page application that consumes the REST API. Sends Bearer tokens with every authenticated request and handles token-refresh logic on 401 responses.

Request Trace
$GET /api/v1/workouts
Bearer token received
JWT signature verified
workouts:read scope confirmed
Ownership rule applied
Service layer queried MySQL
ETag hash generated
200 OK returned
Key Decisions
  • RESTful API following Richardson Maturity Model Level 3
  • JWT authentication with role and scope-based access control
  • ETag support for efficient conditional GET requests
  • Zod validation and strict layered backend architecture
  • Comprehensive endpoint testing with Jest and Supertest

Featured Case Study

Engineering in depth

BackendREST API · Node.js · Koa

SentinelAI

Hybrid Edge–Cloud Violence Detection Architecture

The Problem

Modern fitness applications demand APIs that go beyond basic CRUD — handling complex user hierarchies, enforcing fine-grained access control, and remaining self-documenting at runtime without a separate documentation step.

Architecture Layers

1

Camera FeedContinuous CCTV frame capture feeding into the edge processing pipeline at full frame rate.

2

Edge AI — MobileNetV2Lightweight CNN performing real-time violence classification on-device with minimal compute requirements.

3

Suspicion ThresholdConfidence scoring gate that determines whether a frame warrants escalation to cloud verification.

4

Vision-Language ModelOpenAI Vision API performs multimodal semantic analysis of suspicious frames for contextual verification.

5

Decision EngineFinal classification combining edge confidence scores and VLM verification for reliable event detection.

6

Logging & AnalysisStructured event logging, audit trail, and analytics dashboard for monitoring detection performance.

Key Engineering Decisions

  • JWT with refresh token rotation — zero long-lived secrets in circulation
  • RBAC permission matrix — O(1) authorization checks at every endpoint
  • ETag caching — ~60% bandwidth reduction on read-heavy workloads
  • HATEOAS responses — API is self-documenting at runtime
  • Integration test suite — real database, real assertions, no mocks at data layer

Tech Stack

PythonMobileNetV2OpenAI Vision APIComputer VisionNext.jsTypeScriptTailwind CSSVercel

Read the full case study

Architecture, security, testing, and outcomes

Expertise

Skills & Technologies

Backend

Node.jsKoa.jsREST APIsMySQLJWT AuthRBACHATEOAS

Frontend

ReactNext.jsVue.jsTypeScriptTailwind CSS

Mobile

.NET MAUIMVVMC#Cross-PlatformOffline-First

AI / ML

PythonPyTorchCNNsVideo ClassificationCUDA

Cloud & Infra

SupabaseDockerPostgreSQLOpenAPIVercel

Tools

GitJestPostmanVS CodeSQLite

About

The engineer
behind the work

I build systems with architecture in mind first — thinking about security, scalability, and maintainability before a single line is written.

My focus spans the full stack: from designing secure REST APIs with RBAC and HATEOAS, to building cross-platform mobile apps with offline-first architecture, to training deep learning models for video classification. The common thread is engineering rigour and a preference for systems that actually hold up under production conditions.

I write code to be read by the next engineer — tested, documented at the right level, and structured so that change doesn't require archaeological excavation.

Engineering Principles

Architecture first

Design the system before writing the code.

Security by default

Baked in from day one — not retrofitted.

Test what matters

Integration over mocks; confidence over coverage theatre.

Clean over clever

The next engineer should thank you, not curse you.

3+
Production-grade projects
5+
Core technologies
L3
REST maturity achieved
0
Known OWASP vulnerabilities

Ready to build

Let's build something impactful

I'm currently available for freelance work, contract roles, and full-time positions. If you have a technical challenge worth solving, let's talk.

Contact

Start a conversation

Have a project in mind, a role to fill, or just want to connect? Reach out directly.

Source Code
github.com/Parsa13831383
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