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Full  stack  minded.  AI  driven.

Web apps, mobile apps and AI systems, built with curiosity, care and a habit of shipping.

From notebook to production

Apps, APIs and models

Always learning

Hello from Bandung

Measure, then optimise

I'm Rahardian, a full stack, mobile and AI engineer.

I build things for servers, screens and models.

I started with web apps and REST APIs, then moved into mobile and machine learning. Now I take a product from the database to the app in your hand, and to the model behind it.

In a team, I'm the engineer who takes a feature from the ticket to production: the API, the screen and the model behind it.

I explain trade-offs plainly, keep the team in the loop, and ship work I'm proud to put my name on.

Working  Principles

01

Production, Not Prototypes

A model in a notebook or an API on a laptop helps nobody. I build with the deploy in mind from day one: containers, pipelines, monitoring and documentation, so the work keeps running after the demo.

02

Across the Stack

Frontend, backend, mobile and the AI behind them. Knowing how each layer behaves means fewer surprises where they meet, and better decisions when a problem could be solved in more than one place.

03

Measure Before Guessing

Evaluation metrics for models, tested endpoints for APIs, real devices for apps. Numbers settle arguments faster than opinions, and they show when something is actually better.

04

Small Steps, Visible Progress

Ship small, learn fast, refine often. A working version in your hands beats a perfect plan on paper, and steady progress keeps the whole project honest.

Been thereBuilt that

Experience

Where I have worked and the communities I have helped run, with what I used along the way.

  • Face-swap (deepfake) detection research at the School of Computer Sciences, Penang.

    • Developed a deep learning model for face-swap detection under faculty supervision.
    • Curated datasets and ran training experiments on an NVIDIA A40 GPU server.
    • Validated inference on a Raspberry Pi for edge deployment.
    • Co-authored the findings in an academic research paper.
    • Python
    • Deep Learning
    • Computer Vision
    • Raspberry Pi
  • Project-based, remote: an internal community and finance app for Android and iOS.

    • Built an app with two user roles across five modules: Profile, Worship, Communication, Donation and Syirkah.
    • Integrated the backend and public REST APIs with BLoC state management.
    • Delivered a consistent, responsive UX on Android and iOS from a single codebase.
    • Flutter
    • Dart
    • BLoC
    • REST API
  • Shipped full-stack web apps and REST APIs consumed across web and mobile — with Redis caching, Xendit/Brevo integrations, Dockerized deployments, and GitHub Actions CI/CD.

    • Developed web applications with Laravel, Vue.js and NestJS, and REST APIs with FastAPI for the web and mobile teams.
    • Added Redis caching, the Xendit payment gateway and Brevo transactional email.
    • Administered Linux servers over SSH, containerised apps with Docker and set up GitHub Actions pipelines.
    • Laravel
    • Vue.js
    • NestJS
    • FastAPI
    • Redis
    • Docker
    • GitHub Actions
  • Built ML models for cocoa classification and a RAG pipeline on open-source LLMs, deployed as FastAPI services integrated with IoT devices and consumed by web/mobile teams.

    • Built machine learning models for cocoa classification and prediction.
    • Developed a RAG pipeline on open-source LLMs, improving answer accuracy with prompt engineering.
    • Deployed the models as FastAPI services integrated with IoT devices.
    • Python
    • TensorFlow
    • FastAPI
    • RAG
    • IoT
  • Project-based: Islamic Kids, a native Android learning app for children.

    • Built the app in Kotlin with interactive Lottie animations and child-friendly navigation.
    • Consumed REST APIs with Retrofit 2 and OkHttp, with a Room database for offline access.
    • Published the app to the Google Play Store and owned the release.
    • Kotlin
    • Retrofit
    • Room
    • Lottie
  • Built a generative-AI chatbot with RAG (text/speech/image-to-text) on Gemini, Llama, and Grok, plus n8n/Flowise automation workflows for data-entry tasks.

    • Developed a generative AI chatbot with RAG for text, speech and image input on pre-trained LLMs.
    • Built n8n and Flowise workflows that automate data entry.
    • RAG
    • LLM
    • n8n
    • Flowise

Education

20232027

In progress

B.Sc. Informatics Engineering

UIN Sunan Gunung Djati

GPA 3.83 / 4.00. Expected to graduate in 2027.

  • Placed 2nd in a national-level hackathon among PTKIN universities.
  • Won a gold medal at the NICYMS competition.
  • Coursework strengths: algorithms and data structures, computer networks, databases and IoT development.
  • C++
  • Java

Hard wonWell earned

Recognition

Awards, competitions and the certifications behind the skills.

Expertise

Web, mobile, AI and the backend between them, with the tools I use for each.

ToolsTrade

Toolbox

Four disciplines, each broken into skills, each skill into the tools I use for it. Hover a tool to see where else it turns up.

01Full Stack Web04 skills
01.1

Frontend Development

Fast, responsive interfaces.

01.2

Backend Development

APIs, data and auth.

01.3

Databases

Data that stays consistent.

01.4

Integrations

Payments, email and third-party APIs.

02Mobile Apps03 skills
02.1

Cross-platform

One codebase for iOS and Android.

02.2

Native Android

Kotlin, end to end.

02.3

Integration & Release

Connected and shipped.

03AI & RAG Systems04 skills
03.1

Machine Learning

Models that survive production.

03.2

LLM & RAG

Answers grounded in your data.

03.3

Model Serving

Models behind an API.

03.4

AI Automation

Workflows that run themselves.

04APIs, IoT & DevOps04 skills
04.1

API Development

Secure, documented endpoints.

04.2

IoT

Devices that report in.

04.3

DevOps & Servers

Deployed, repeatable, monitored.

04.4

Performance

Fast under load.