curaJOY

Software Developer | May 2024 - Present

MyCuraJOY Website

• Developed an inclusive, gamified, and AI-assisted platform for enhancing family behavioral wellness, building 10+ reusable UI components with React, Next.js, TypeScript, and PrimeReact, while enhancing UI with Tailwind CSS.
• Enhanced user-interactive 3D avatars with Three.js, incorporating animations, advanced visuals, and seamless integration with a sophisticated behavior, mood, and body check-in system, boosting user satisfaction by 40%.
• Built and optimized reward and check-in systems with Redux modules, handling asynchronous data fetching, complex state updates, and user interaction logic, resulting in a 20% improvement in app performance and increased retention rates.
• Operated in an Agile(Scrum) environment using Jira to manage sprints, accelerating development cycles and delivering new features and releases more frequently through improved team coordination and project management.

Technologies

React Next.js TypeScript Three.js Redux Tailwind CSS PrimeReact Agile(Scrum) Jira Ready Player Me Jest Git

Orbiz.app

Software Engineer Intern | April 2024 - Present

Orbiz.app Website

• Developed an LLM-powered, data-driven platform and a Chrome extension to streamline influencer outreach and campaign creation, reducing manual effort by 15 hours/week and improving marketing campaign efficiency.
• Designed and implemented scalable database schemas using PostgreSQL and TypeORM, leveraging hierarchical relationships and entity mappings to optimize complex workflows for campaign creation and influencer matching.
• Integrated APIs with Azure OpenAI to scrape websites, analyze products to generate campaign suggestions and relevant tags.
• Designed and deployed REST APIs with Node.js, Nest.js, Express and TypeScript, enabling efficient influencer querying, exporting, and tag-based matching across 3,000,000+ records in under 4 seconds using optimized SQL queries.
• Orchestrated dual AWS RDS connections with Docker containers, managed CI/CD pipelines via GitHub Actions and AWS CodePipeline on ECS, and configured IAM task roles with execution policies for secure and dynamic access to AWS resources.

Technologies

Node.js Nest.js Express TypeScript REST API PostgreSQL TypeORM Prisma Docker AWS Azure OpenAI GitHub Actions AWS ECS AWS CodePipeline AWS IAM AWS RDS CI/CD Git Chrome Extension

Tellus AI Assessment Platform

Software Developer, Capstone Project with CUHK KEEP Team

Supervisor: Irwin King, Professor, CUHK | Sep. 2022 - April 2023

Product Introduction | Website

• Designed and constructed E-R diagrams, UML class diagrams, and database schema based on use cases.
• Integrated Microsoft Azure AI Face Service and Python libraries/frameworks (e.g., OpenCV, MediaPipe, DeepFace) to facilitate facial, emotion, accessory, and body language analysis, boosting analysis accuracy by 30%.
• Utilized React, TypeScript, and Material UI to create real-time camera calibration feature and visualization dashboard.
• Developed algorithms using Python for interviewee presentation skills auto-evaluation and cheating detection.
• Designed scoring & commenting algorithms to achieve 93% analysis accuracy and 40% faster runtime.
• Designed 100+ unit and integration tests using Pytest for application testability and security, keeping 80% code coverage.
• Employed REST APIs for video management and implemented CURD operations on evaluation results using MySQL.

Technologies

Python Microsoft Azure Machine Learning Computer Vision Video Analysis Software Engineering System Design React Material UI Node.js MySQL JavaScript/TypeScirpt Git REST API

Deep Learning-Based Time Series Analysis and Forecasting

Summer Research Intern & Term-time Student Helper, CUHK Reliable Computing Lab

Supervisor: Qiang Xu, Professor, CUHK | May 2022 - Oct. 2022

• Built a large-scale repository for time-series analysis and forecasting on GitHub, including different state-of-the-art deep learning models
• Collaborated on creating a systematic pipeline to utilize and evaluate time series prediction models, implementing unified data preprocessing procedures, model instantiation interfaces, and standardized evaluation procedures
• Reproduced and implemented various spatio-temporal traffic prediction models and dataset loaders; modified the models to be compatible with repository interfaces, configurable, and adaptable to different datasets and tasks
• Implemented model evaluations and comparisons to ensure the characteristics and the original results of the models are well preserved

Technologies

Python PyTorch Linux Machine Learning Deep Learning Time-series Forcasting Anaconda Git

Simultaneously Deblurring and Segmentation for Cataract Surgical Instruments

Summer Research Intern, Surgical Robotics and Instrumentation Lab, CUHK

Supervisor: Shing Shin Cheng, Assistant Professor, CUHK | June 2021 - Sept. 2021

• Worked on a spatio-temporal information-based network for cataract surgical instrument segmentation, consisting of a deblurring module and a subsequent segmentation module, with PyTorch and TensorFlow frameworks
• Improved the performance of the segmentation network by incorporating leading-edge deep learning modules
• Designed and conducted experiments on model evaluation and comparison, successfully proved the strength of the network under different special scenarios
• Designed and constructed a cataract surgical instrument dataset for integrating both deblurring and segmentation procedures to demonstrate the holistic novelty of the network
• Investigated the background and current state of research in the field of surgical skill assessment, proposed the motivation and the future research directions for the project

Technologies

Python TensorFlow PyTorch Docker Linux Anaconda LaTeX Machine Learning Deep Learning Computer Vision