Hello World! I'm Jonathan Lim.

Autonomous Racecar is a project which aims to build an autonomous vehicle based on the F1tenth standards that can run by itself on any track, with integration of various software algorithms. The main interface/operating system used in the project is ROS or Robot Operating System, where all the software is tested and uploaded onto the autonomous vehicle. My main task is to implement Google Cartographer as our main Simultaneous Localization and Mapping (SLAM) algorithm and Adaptive Monte Carlo Localization (AMCL) to localize the vehicle, and assist my teammates in implementing pathfinding and obstacle avoidance algorithm.

Machine Learning for Disease Prediction is an UROP-funded project that makes use of an interactice web application and different machine learning algorithms to display and predict patients' skin diseases based on the data collected about their symptoms/traits. My task was to build a simple, interactive full-stack web application capable of displaying patients' information with the provided patient's name using the React framework, Node.js, Express.js, and MongoDB, as well as to research about the machine learning algorithms to be used for the project.

Related Links:
Undergraduate Research Opportunities Program(UROP) Poster

1kWh Challenge is another project from CalPlug to educate and demonstrate to middle schoolers about the importance of saving energy and being aware about how much energy is consumed by electronics through the use of a web application. The demonstration of the project works like a game where the middle schoolers will either earn or deduce points based on how much energy they generated or consumed at each game station, and compare points with others at the end of the demonstration. My task was to assist in the completion of the web application using Javascript and the AngularJS framework, and to manage the workflow of the demonstrations.
P.S. I am not at the liberty to share the source code or any more detailed information of the project.

Related Links:
Game Operation Guides

Safe Passage Electronic Force Monitor is a medical device project from CalPlug, an on-campus organization I have been part of since the winter of my freshmen year. The purpose of the project is to build a FDA-approved medical device prototype to be tested by the Department of Urology at UC Irvine that is capable of monitoring the amount of force being exerted on patients during urinary surgeries. I was initally an Android developer under the project who helped build the project's first native Android application using Java, and later became the project's team lead who both built the React Native version of the Android application and oversaw the logistics of the project until its completiton in the early Fall of 2018.
P.S. I am not at the liberty to share the source code or any more detailed information of the project. However, I have shared one key technology to the success of the project below.

Related Links:
Project Poster
Espressif ESP32 with BLE Demo
Images Related To Project

MilkyWay was a business venture I co-founded with two of my college friends that uses an Android application to help small to middle businesses retain their customers with our own customer loyalty program at POS. I acted as the CEO and main frontend developer of the project who built both the native and React Native version of the Android application and managed the business development/branding, logistics, and team dynamic of the project.
P.S. The project was left on hold after we all agreed on focusing on schoolwork instead.

Related Links:
App Demo
Business Plan

As part of the Udacity Data Science Nanodegree program, I had the opportunity to work on 3 machine learning projects for its first term. The first project was based on supervised learning, second one was based on deep learning, and last one was based on unsupervised learning. For more information about each one of the projects, click the GitHub links below to see the source code!

In the second term of the Udacity Data Science Nanodegree Program, I had more practical & hands-on projects that show how data science would be in the workforce. I wrote a Medium data science blog post, focused on essetial software & data engineering skills to build a machine learning pipeline, and learned about how experimental design & recommendation engines work. Last but not least, I finished this nanodegree program with a capstone project on big data processing & modeling with PySpark. Click the GitHub links below to see the source code for more information about each one of the projects!