I am a third-year Computer Science student at Simon Fraser University, with a passion for web development, software development, front-end design, and full-stack applications. I specialize in React, JavaScript, and Python, with experience in backend technologies like Node.js and database management using SQL. I enjoy building interactive and scalable web solutions. Beyond technical skills, I thrive in team-oriented environments and enjoy problem-solving, mentoring, and collaborating on innovative ideas. I seek opportunities to apply my knowledge in internships, software development roles, or open-source contributions.
| Project | Description | Tech Stack |
|---|---|---|
| π½οΈ FoodConnect | A donation platform connecting food donors and recipients, with real-time chat, filtering, secure login, and map integration. | React, TypeScript, Tailwind CSS, Express.js, PostgreSQL, AWS |
| π‘οΈ DeepPhishing | AI-powered phishing detection and quiz platform for educating users using email, file, and link analysis. | Next.js, Tailwind CSS, Shadcn/ui, OpenAI API, JavaScript |
| π SportoQuiz | A sports trivia app generating AI-powered questions with a live leaderboard and CI/CD pipeline. | Next.js, TypeScript, Tailwind CSS, OpenAI API, Supabase |
| π SFU Marketplace | The exclusive marketplace for Simon Fraser University students. Buy, sell, and trade with confidence within the SFU community. | Next.js, React, JavaScript, Tailwind CSS, JWT Auth |
| π©οΈ SFU StormSage | Python Twitter bot for weather, parking, and road alerts at SFU, scraping and posting real-time updates. | Python, BeautifulSoup, Twitter API |
| π» Personal Portfolio | A fully responsive personal site with animated transitions, project highlights, courses page, and contact info. | Next.js, TypeScript, Tailwind CSS, Once UI |
| π¬ MovieMind | Movie recommendation system using TF-IDF and cosine similarity, with a GUI built in Tkinter. | Python, Pandas, Scikit-learn, Tkinter |
| π NBA Games Prediction Model | Machine learning model that predicts NBA game outcomes using scraped box score and standings data. | Python, Scikit-learn, Pandas, Matplotlib |


