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Zen Mode Extension is a Chrome browser extension that I developed to optimize productivity and minimize distractions. It empowers users to regain control over their online experience by blocking access to up to 5000 domains. As a testament to its versatility, this extension also boasts a search functionality, enabling users to effortlessly search for and unblock specific websites that may be temporarily restricted. By integrating comprehensive website blocking features with a user-friendly search function, Zen Mode Extension offers an efficient solution for enhancing productivity and maintaining focus during web browsing.

Zen Player

Zen Player is a side project, I am currently working on. It is a video player focuses mainly on preventing users from spending more time than it should be on YouTube videos. Due to YouTube recommendation, we often tend to watch more videos than we originally came for. Thus, lots of time wasted on watching videos that are not related to our search intention. The main features I am currently working on includes ability to search videos by name or url on YouTube, provide analytics on watch time, allow maximum watch timer for each day, allow creating queues and looping of videos. It will be available on both web and android.

Portfolio Website (This One)

This portfolio website is built using both Gatsby.js and Tailwind CSS. I also enabled DevOps using GitHub Actions which deploy the website to GitHub Page every time I push code changes to a specified branch. I built this website as an opportunity to learn two technologies I have been wanting to learn, Gatsby.js and DevOps.

Tensorflow Implementation of CAN

I built this project as my graduation thesis and also a way to learn in-depth about Tensorflow. I forked from the original repo and worked on Tensorflow implementation of Creative Adversarial Network (CAN) model which generates creative art works by training upon art styles dataset. My main contribution for the project includes;
  • Up-scaled Generator model output image by 2 times, including its neural network Parameters. (from 256x256 to 512x512)
  • Transformed the code structure to a single file that can be trained on Google Colaboratory.
  • Created trained checkpoint files for both original resolution model (256x256) and enhanced resolution (512x512) model.
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