Chantelle Troutman

Computer Science Student

University of California, Santa Cruz

Technical Skills

Languages

  • C
  • Python
  • Java
  • JavaScript
  • Haskell
  • HTML / CSS

Tools

  • Git / GitHub
  • VS Code
  • Android Studio

Concepts

  • Data Structures
  • Machine Learning
  • Functional Programming
  • Assembly

Crafts

  • Welding
  • Sewing
  • Knitting
  • Fabrication
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Senior Thesis · Phase 1

Luna Yoga

The app aims to integrate moon phases and menstrual cycles with yoga practices to provide a personalized wellness experience. In Phase 1, the focus was on developing the front-end interface, allowing users to view and interact with the core features. All visual elements and navigation are now fully implemented, laying the foundation for future phases where recommendations and personalized experiences will be added.

React Native · Node.js · Supabase 2025 Solo Project
01 / 04

Login Screen

Minimal login with secure authentication.

02 / 04

Collective

Dashboard with streaks and recommendations.

03 / 04

Settings

Customize experience and preferences.

04 / 04

Yoga Types

Explore yoga styles and sessions.

Capstone Class/Project · CSE140

PacMan: Capture the Flag

Developed intelligent agents for a competitive Capture the Flag variant of Pac-Man. The project required designing both offensive and defensive agents capable of strategic decision-making in a dynamic, adversarial environment. Our team implemented the A* search algorithm to optimize pathfinding and real-time gameplay decisions. The agents successfully competed against other teams, earning 5th place in the final tournament.

Written Report

Demo Walkthrough

In this demo, the agents on the red team navigate the maze in real-time using A* pathfinding. The offensive agent focuses on collecting food and capturing the opponent’s flag, while the defensive agent guards our territory and intercepts opponents. Watch how A* allows intelligent movement around obstacles and dynamically reacts to the blue team’s actions.

This setup highlights key AI strategies such as risk assessment, threat evaluation, and cooperative behavior. The red team agents are designed to outperform the baseline blue team, demonstrating both competitive dynamics and advanced AI decision-making in a live game environment.