Hi, I'm Ken.

I am a student at Cornell University studying computer science, and I like to bring cool ideas to life with software.

Picture of me at death valley

About

I am a second year student at Cornell University studying Computer Science and Operations Research and Engineering. Some areas of computer science I'm interested in includes software development, front-end and machine learning.

Besides being a student and developing projects, I...

You can contact me at my email kchiem12@gmail.com. Below are links to my LinkedIn and GitHub.

GitHub LinkedIn

Experiences

cornell-logo cornell-logo cornell-logo

Research Assistant @ Cornell University

  • Created web GUI to assist labeling objects in order to solve the Abstraction and Reasoning Corpus (ARC)
  • Gathered and summarized statistics on various ARC problems
  • Worked alongside another undergraduate under Kevin Michael Ellis

jQuery | Python | NumPy | Matplotlib

Vision Subteam Dev @ Cornell Cup Robotics

  • Developing calibration/detection of April Tags for MiniBot overhead vision system
  • Reduced median error in position and angle detection by ~20%

OpenCV | Python

Web Developer @ ACSU

  • Revamping current website for the Association of Computer Science Undergraduates (ACSU)
  • Reworking Resume Book webpage form

HTML | CSS | JavaScript | Firebase

Portfolio

SideQuest

App to find gigs; won best overall in AppDev HackChallenge

Swift

In the span of two weeks, I, along with a group of four others, this app, where users can log in and post gigs, and search for gigs to do. I mainly did the front-end, using Swift and XCode.

I used Alamofire to connect the backend in order to save user info and gigs.

Github
sidequest-login
sidequest_profile_screen

Routinely

A web-based application to track your workouts

React Node.js MongoDb Redux

Created in August 2022, the application is made with MERN stack. It authenticates the user, and maintains a calendar of the users activity/workouts using a RESTful API. In December 2022, the project transitioned from Firebase to MongoDB as it's database.

Gtihub
workout-signup
workout-adding
workout-dashboard

Railroad Damage Detection

Detects defective railroads with machine learning

Python

Created in August 2022. I used PyTorch in order to create a model that detects a defective railroad given an image. Through training the model, it resulted in an accuracy of 94.33% on the training set, and 77.27% on the test set.

Gtihub
railroad_detection_result

VWC Nails Website

Webpage for a nail salon in Philadelphia

HTML5 CSS3 JavaScript

Created static, responsive website for VWC Nails in Philadelphia. If you ever find yourself in Philadelphia, do check it out!

VWC
vwcnails_homepage

Made with heart-icon by Kenneth Chiem © 2023

GitHub LinkedIn Mail