I created this website to showcase my projects and experience, also mostly just because I was bored and wanted a fun build. I'm always looking for ways to upskill myself, especially when it comes to tech, data, and AI.

I am a massive sports fan, particularly with Manchester United and LeBron James. If you ever want to debate match results, stats, or basketball takes, I'm always down to chat.

I also love exploring random cities when I travel, so I'm planning to use this site as a little corner of the internet to post and share more of my travel photos, too.

In my free time, I enjoy diving into data-driven projects that blend analytics, prediction, and storytelling. Whether it is analyzing MVP trends, debating the GOAT in basketball, or putting together an analytical dashboard to track lottery numbers I love using data to explore ideas and uncover insights.

• AI Expense Tracker: AI expense tracker that logs spending from Telegram messages and gives monthly spending reviews.
• NBA MVP Prediction: Predicting MVP outcomes using machine learning and season stats.
• LeBron vs Jordan Analysis: Deep-dive player comparison based on data and era-adjusted metrics.
• Toto Dashboard: Interactive number analysis and tool.

I built a Telegram bot that lets me log expenses as plain-text messages, like "12.50 kopi at foodcourt." An LLM extracts the amount, category, and description, and writes it straight into a Google Sheet, no app, no forms, just a text message.

At the end of each month, I ask the bot for a review, and it compares spending across categories and tells me, in plain language, where I overspent and what's worth cutting back on. The whole thing runs on free-tier infrastructure (Google Apps Script, Gemini API), with no backend or hosting cost.

As a basketball fan and data enthusiast, I was curious whether we could predict MVP shares using players and teams season stats. This curiosity led me to build a machine learning model that forecasts MVP voting outcomes based on historical data.

I experimented with an ensemble model (Linear Regression, Gradient Boosting, XGBoost). Throughout the project, I focused on model interpretability, cross-validation, and feature importance to understand which metrics truly influence MVP results.

The LeBron vs Jordan debate has always been filled with strong opinions, so I wanted to cut through the noise and approach the question from a more analytical angle. Using a blend of statistics, historical context, and weighted metrics, I compared the two players across career longevity, regular season dominance, playoff success, and awards.

I built this as a structured, data-first deep dive to spotlight patterns fans often overlook, like how scoring trends changed by era. Beyond just the stats, the project pushed me to think critically about framing narratives with data and storytelling.

This project is an interactive analytical dashboard built to explore historical Toto results and statistics. Because each draw is completely independent of the past, this tool isn't about beating the odds or promoting gambling. It is purely a fun way to dive into data, numbers, and frequency stats.

The dashboard lets you explore past draw trends and visualize data in one place, serving as a practical, lightweight example of applying data analytics to random numbers just for the sake of curiosity and good engineering.

I thought this would be a nice way to log my travels since I have a website. (Not a blogger)