Yu Cheng Wei

Hi! I'm

Yu Cheng (Julian) canada

My LinkedIn profile My Github profile
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Experience

Teacher Assistant
Personal Projects
School Projects
Hackathon
Game Jam

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Education

B.Sc. Bachelors of Computing
GPA: 4.10

queens

Hi, I'm Yu Cheng (Julian) and I am an aspiring software developer and a Computer Science student at Queen's University. Through personal work, school work and developer events (Hackathons, Game Jams), I have developed proficiencies in various programming languages and concepts. Below you can see some of my skills and self made projects.

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Programming Skills

Frontend Development

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HTML

Experienced

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CSS

Experienced

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JavaScript

Basic

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TypeScript

Basic

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Angular

basic

Backend Development

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MySQL

Basic

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Flask

Basic

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Django

Basic

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Git

Experienced

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Express JS

Basic

Other

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Python

Experienced

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Java

Intermediate

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C++

Intermediate

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C

Basic

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Unity

Basic

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My Projects

Project 1

CCASM Database and Query Service

Database and Query service website built for a group of Canadian biology professors.

Throughout the course of 8 months, our school team communicated, designed, and implemented the website. Taking in great consideration of user feedback. Key services including browsing, interactive maps, customer handling, and database editing.

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QBnB Agile/Scrum Project

Project focused on learning and practicing Scrum, and Agile procedures.

A four month long project building an AirBnB site; consisting of 10 scrum sprints involving daily scrum meetings, code reviews, and github actions. All under the supervision of our professor.

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Mountain

Dark Wave

Game designed for Development class

Designed and developed a term long 2d Unity game focused on limited vision and the dark with a team of 3. Assumed a leadership role at weekly meetings, ensuring consistent progress and resulting in a high grade (95+).

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Project 4

Pneumonia Detector

Software developed for QHacks Hackathon 2024.
Prompt: Artificial intelligence.

Using keras, I developed a program which trains and predicts pneumonia in x-ray images of the chest. The program mainly uses convolution neural networks and has a prediction rate of over 90 percent in testing.

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Contact Me