Student_2026: Foundational Template for Student Portfolios

Student_2026 is a Jekyll-based GitHub repository I developed as a professional, fully customizable template for student portfolios in our AP CSP course. It allows peers to showcase their blogs and projects without needing to set up anything from scratch.

My Role

  • Sole developer and systems designer of the repository structure and theme.
  • Authored documentation and usage guides for seamless onboarding.
  • Maintained version control and handled updates based on user feedback.

Tools & Technologies

  • Jekyll: Static site generation.
  • Git & GitHub: Version control and project-wide issue tracking.
  • Liquid / HTML / SCSS: Theming and layout customization.
  • GitHub Pages: Zero-setup site hosting.
  • Markdown: Content formatting and post structure.
  • VS Code: Primary development environment.

What I Learned

  • Deep understanding of GitHub Pages and Jekyll pipelines.
  • Experience designing reusable infrastructure at scale.
  • Skill in writing developer-first documentation and helping others deploy with confidence.

Club Hub: Interest-Based Club Recommendation Engine

Club Hub is a smart club recommendation tool for high school students. It takes user interests, compares them to club profiles, and ranks the most relevant ones using a live-updating interface.

My Role

  • Scrum Master and algorithm developer.
  • Oversaw sprint planning and peer coordination.
  • Designed frontend logic and assisted with API design.

Tools & Technologies

  • JavaScript / HTML / CSS: Frontend layout and dynamic sorting.
  • Git & GitHub Projects: Issue tracking, branching strategy, and pull request management.
  • Postman: For testing API endpoints and validating backend responses.
  • Agile Development: Stand-ups, velocity tracking, sprint retrospectives.
  • Figma: UI mockups and early design discussions.

What I Learned

  • How to handle asynchronous updates and sorting in pure JS.
  • Best practices for testing APIs and visualizing responses with Postman.
  • Practical project management under Agile constraints and short timelines.

SD IMOP (San Diego Infrastructure Management Optimization Platform)

SD IMOP is a machine learning platform designed to forecast infrastructure maintenance using city data. It unifies disparate data sources, performs intelligent forecasting, and outputs actionable insights via a dashboard.

My Role

  • Project Lead — handled all modeling, data prep, and frontend UI development.
  • Created reproducible data pipelines and facility-level predictions.
  • Communicated with potential city stakeholders for real-world deployment.

Tools & Technologies

  • Python (Pandas, NumPy): Data cleaning, transformation, and prep.
  • XGBoost / Random Forest (via scikit-learn): Predictive modeling and tuning.
  • Flask: RESTful backend for model integration and predictions.
  • JavaScript (Vanilla): Interactive frontend dashboard.
  • CSV + JSON Pipelines: For handling real-world datasets and formatted exports.
  • Postman: Endpoint testing during Flask backend development.
  • Git: Branching, commits, merges across frontend/backend components.
  • Google Sheets + FCI APIs: Raw data ingestion and normalization.

What I Learned

  • End-to-end architecture design for civic ML applications.
  • Experience translating raw city datasets into feature-rich ML-ready inputs.
  • Mastery of Flask backend deployment and JavaScript-based frontend coordination.

Skills and Tools Demonstrated

  • Git & GitHub: Branch management, pull requests, and repo coordination.
  • JavaScript: UI logic, filtering, interactivity.
  • Postman: API testing and request/response debugging.
  • Flask: Lightweight backend for data science pipelines.
  • Jekyll + Liquid: Static site development for templated portfolio systems.
  • Machine Learning: Practical use of XGBoost, Random Forest, and structured feature engineering.
  • Agile Workflows: Scrum ceremonies, sprint planning, retrospectives.
  • Documentation & Onboarding: Clear, reusable guidance for peers.

These projects were built not only with methods and vision, but with a robust technical stack that reflects real-world development, testing, and deployment practices. Each tool and platform was chosen intentionally — not just to build something functional, but to ensure maintainability, scalability, and user empowerment.