Hello and Welcome!

My name is Ivan CHAN

And I'm a

I am a lifelong learner with a deep passion for software engineering and a relentless drive to innovate.

Graduating with First-Class Honours in Computer Science from City University of Hong Kong, I was proud to earn multiple scholarships and secure a spot on the Dean’s List for several times, reflecting my commitment to excellence.

With a keen enthusiasm for web and mobile application development, I thrive on tackling complex challenges, learning new skills rapidly, and delivering creative, high-quality solutions.

I am driven by the opportunity to make an impact and continually push the boundaries of what’s possible in technology.

I am excited to collaborate with like-minded individuals and contribute to shaping the tech future, one innovative solution at a time.

My Skillsets

🌟Client-Side

Android Studio (JAVA) for Android Native

React JS for Web App

React Native for Android Native & iOS Native

Angular for Web App

🌟Server-Side

NodeJS & ExpressJS & NestJS

ASP.net Core (C#)

🌟Database

MS SQL Server

MongoDB

🌟Other Tools

Git & Github

Postman

Visual Studio

VS Code

Projects Showcase

🌐Web Application

To Do List Web Application

This is a full-stack web application built using MongoDb,ExpressJS,NodeJS and ReactJS (MERN stack). It supports basic CRUD operation, user authentication using passportJS & JWT, and Image Uploading operation.

Digital Business Card Web Application

This is a full-stack web application built using MongoDb,ExpressJS,NodeJS and ReactJS (MERN stack). It supports registration (with email verification), login, logout, 'change password', 'forget password' (with reset password email), 'Contact site owner'. The Main feature is "Business Card Generation". It provides a form for user to fill in and help generate V-card such that users can download it into their contact book.

📱Mobile Application

To Do List Android Native Application

This is full-stack android native application built using AndroidStudio, Nodejs, Expressjs, MS SQL server. The API created using nodejs demonstrate how we can perform CRUD in MSSQL database using plain query & stored procedures.The api follows MVC design pattern and preform CRUD on the Task Object in database. Meanwhile, The frontend android application use Retrofit Library for calling the API

To Do List React Native Application

This is full-stack react native application built using ReactNative, Nodejs, Expressjs, MS SQL server. The API created using nodejs demonstrate how we can perform CRUD in MSSQL database using plain query & stored procedures.The api follows MVC design pattern and preform CRUD on the Task Object in database. Meanwhile, The frontend android application use Axios Library for calling the API and performing CRUD operations.

Mark Your Loan (Mark數/記帳小工具) (avaliable on Google Play)

This is a mobile application with only frontend built. It is built using React Native and sqlite as local storage database.

Mark Your Loan is an application which allows users to record the amount they borrow from friends and the amount they help friends to pay. The application is simple and easy to use, users can insert borrowing records and helping records, view the list of records at anytime. They can also select a specific friend to see the records related to that friend. The application supports English and Chinese.

(Mark數/記帳小工具) 是一個可以用于記錄帳目的應用程式。程式簡潔易用，用家可以輸入借款紀錄、幫朋友付款的記錄，便可以將相關紀錄儲存於手機內，隨時查閱，用家更可以選擇某位朋友，查看有關他的借款和幫助紀錄。程式提供兩種語言(英文及中文) ，可于設定內選擇。

Library Management System

This is a full-stack application built using Android Studio (Java) as frontend and node &express &sql server as backend. This application simulates the daily borrowing and return process of library transactions.

📈Data Science Project

Study on hierarchical clustering

This project implements hierarchical clustering on the wine dataset. It foucuses on studying the differences in hierarchical stuctures generated using single link, complete link and group average. We also make comparison with the clusters formed using k-means and the clusters formed using subset of attributes.

YouTube Spam Classifier

This project adopts different methods in classifying spam comments, which includes Logistic Regression Model,Recurrent Neural Network (LSTM), K-nearest neighbor, Decision Tree Classifier and Support Vector Machine (SVM)