-Developed a YouTube extension integrating AI-powered chat, quiz generation, and summaries within a team of 8.
-Contributed to both frontend and backend development.
-Implemented clean architecture and security best practices for backend services using Go.
-Optimized caching mechanisms by utilizing Redis
-Conducted API testing to ensure integration reliability.
-Practiced CI/CD pipeline using GitHub Actions for automated staging deployment on Amazon EC2.
-Gained hands-on experience with IaaS, including Amazon EC2, Docker, and ElastiCache, testing deployments and
understanding containerized backend infrastructure.
-Project sponsored by Riipen through the Advance Ontario program.
-Relevant skills: JavaScript, Go, Redis, team collaboration

-Developed a tic-tac-toe feature in a social health app, encouraging users to engage in random acts of kindness.
-Built the frontend using Flutter, focusing on a smooth user experience.
-Assisted in backend debugging using Node.js and MySQL.
-Set up a home server(Ubuntu) to host the Node.js backend for testing.
-Relevant skills: Flutter, MySQL, team collaboration, Linux

-Led a team of 3 in developing a Twitter like social platform supporting posts, comments, and likes.
-Managed project timelines and tasks using linear.app;
-Implemented RESTful APIs using Express.js and MySQL; built responsive UI with React.
-Integrated Google OAuth for secure user authentication; deployed the full stack on Google Kubernetes Engine(GKE)
with CI/CD pipeline using Github Action/Google cloud build trigger.
-Utilized Google Cloud Storage for image uploads and Google Cloud SQL for managed database hosting.
-Relevant skills: Team Management, Google Kubernetes Engine, DevOps

-Researched and analyzed the correlation between EEG signals and Heart Rate Variability (HRV) in a team of 3.
-Pre-processed EEG and ECG signals using multiple techniques to assess potential correlations.
-Selected key Power Spectral Density (PSD) features from specific brain regions and frequencies for analysis.
-Trained and fine-tuned a Feedforward Neural Network (FFNN), achieving 68% test accuracy.

-Designed and implemented a MariaDB database inspired by Rakuten Kobo’s eBook system.
-Modeled entities and relationships using ER and relational diagrams; applied normalization from 1NF to BCNF.
-Collected and populated realistic book and user data through web scraping to simulate platform behavior.
-Produced a final presentation demonstrating schema design, normalization process, and query performance.
-Relevant skills: MariaDB, SQL, ER modeling, normalization, web scraping

-The purpose of this project is to forecast the results of the Canadian Federal Election, focusing on the Liberal and
Conservative Parties as part of a group of four.
-Executed data cleansing procedures on census and survey information prior to post-stratification.
-Performed exploratory data analysis (EDA) to assess the pattern of key predictor variables.
-Employed survey data to fit two logistic regression models predicting the respective possibilities of victory for the Liberal
Party and the Conservative Party.
-Conducted post-stratification analysis utilizing census data in order to estimate the likelihood of the Liberal Party and
Conservative Party, respectively, securing victories among the general population.
-Relevant skills: R, logistic regression, groupwork

-Developed and iterated on a personal website since 2016, evolving from static HTML/CSS to modern React-based architecture with responsive design and reusable components.
-Introduced JavaScript in 2022 for interactivity and Bootstrap in 2023 to streamline styling and improve layout responsiveness.
-Optimized performance through image compression, CSS/JS minification, and frontend best practices.
-Managed domain configurations and deployed multiple subdomains (e.g., Hugo blog, PeerTube) to demonstrate hosting
flexibility and DNS management skills.
-Relevant skills: HTML, CSS, JavaScript, Bootstrap, React, DNS/subdomain configuration, self-hosted platforms