Hi, I'm a second-year computer science student at UC San Diego with experience and skills in front-end web development, AI, and Machine Learning. Having a passion for learning new things, I am always seeking out opportunities to learn new technology and cutting-edge solutions both inside and outside the classroom.

In my spare time, I like to explore new genres of music and play instruments too! Currently working on learning guitar by myself.

Email: [email protected]
LinkedIn: https://www.linkedin.com/in/edward-lin-s/

World Wiser Sport Committee (WWSC) | Full Stack Web Developer

• I worked as a full stack web developer for WWSC, a non-profit that promotes Wiser Sport worldwide by training referees and hosting international tournaments.
• I planned and designed the official WWSC website with Figma to create multiple prototypes.
• The previous website had a long loading time, so I redesigned responsive front-end interfaces with React.js to reduce the loading time. Styled the website with Bootstrap CSS.
• Used front-end client (React.js) to fetch content from existing WWSC WordPress backend by accessing WP REST API endpoints.
• Currently, building a referee registration system using Google Firebase authentication, storage, and NoSQL Firestore database services to allow 400+ referees to edit/update profiles, upload/track their game records, and create a data visualization dashboard (Google Charts).

Triton Software Engineering | Software Developer

• I worked as a front-end developer with a cross-functional team for the nonprofit Fixnation's landing page, creating a responsive masthead, roadmap, mobile stats page, and interactive quiz components.
• I used HTML, CSS, Typescript, and SvelteKit to develop the website.

Comet College Applications Task Manager | Software Engineer Intern

• I provided strategic software consultation and analyzed UI/UX to help test and improve the platform for public use.
• During my time as an intern, I researched and reported findings on improving Comet’s search engine performance with inverted indexing and NoSQL databases, developed a Python picture-to-JSON transcript reader that converted images into data structures to make reading transcript info faster and easier, and created a chat app using CometChat widget and Firebase to allow one-to-one counseling.

ReViSE: Reconstructing Visual Stimuli from EEG Signals

• Created a generative deep learning model using PyTorch to reconstruct the images from 128-channel EEG data.
• Applied an LSTM model to extract visual features from 20,000 EEG data and inputted the processed data into a Deep Convolutional Generative Adversary Network to train and generate images.
• Developed model for possible future applications such as allowing the paralyzed to communicate, forensic analysis by identifying suspects, and dream visualization.

ToiFall: Wifi CSI Activity Recognition

• Classification machine learning model with Python to detect elderly restroom falls with 80% accuracy. Took Channel State Information (CSI) as input and used Support Vector Machine Classification to identify the type of action the CSI recorded.

Visual Question Answering App

• Python program utilizing a Convolutional Neural Network Long Short-Term Memory Model (CNN-LSTM) to help the visually impaired distinguish their surroundings. Used question text and image as input to return sentence output.

Facial Emotion Detection Project

• Python computer vision program using CNN to accurately classify five facial emotions for individuals with autism spectrum disorder to identify human emotions.

• Languages: Java, Python, C, ARM Architecture, JavaScript, TypeScript, HTML, CSS, SQL, Kotlin, Svelte, R
• Technologies: Git, React.js, GitHub, JUnit, Bash, Figma, NumPy, Pandas, PyTorch, WordPress, Tableau, LaTex, VSCode