Lecturer · System Builder · Data & AI Practitioner
I design small, practical systems that make data and AI useful in real work, not just slides.
I build simple, reliable systems for education, data work, and AI-assisted tools. My focus is on clarity, usefulness, and solutions that are small enough to deploy and real enough to be used.
HTML, CSS, JavaScript
For clean, accessible interfaces that stay lightweight and easy to maintain.
Firebase, basic Node.js
For small, maintainable backends that are quick to ship and monitor.
Python, Pandas
For preparing, cleaning, and exploring datasets before they reach dashboards or models.
ML basics, LLM APIs
For focused, task-oriented AI features instead of overcomplicated pipelines.
GitHub, Google Colab, Firebase Hosting
For fast iteration, quick experiments, and straightforward deployment.
These are not “concept only” projects. Each one is built to run, to be tested, and to show how small systems can still be useful.
Firebase · Web App · Data Entry
A simple Firebase-based web app for managing academic data: records, updates, and basic reporting. Built to demonstrate clean data flow, minimal UI, and a straightforward system structure.
View DemoLLM API · Text Processing
A lightweight demo that sends short texts to an LLM API for analysis: tagging, summarizing, or basic classification. The focus is on understanding the workflow and integration, not on training models.
View DemoData · Charts · Insights
A small dashboard for visualizing business data with simple, readable charts. Designed to turn raw rows into quick insights that non-technical users can understand.
View DemoLecturer in Digital Business with a background in Information Systems. My academic work focuses on data analytics and applied AI in education, especially how small systems can meaningfully support learning and decision-making.
What I’m currently testing, iterating, and learning from: