Machine Learning Engineer with a focus on computer vision and deep learning algorithms. Vanderbilt University Computer Science graduate experienced in developing high-precision object detection models and reinforcement learning systems.
- Machine Learning Frameworks: PyTorch, TensorFlow, scikit-learn
- Computer Vision: YOLOv5, Object Detection, Transfer Learning
- Reinforcement Learning: Policy Optimization, Environment Modeling
- Languages: Python, TypeScript, JavaScript, C++
- Web Development: React, Astro, Node.js
🏉 AI-Powered Rugby Element Detection - Real-time object detection with 90%+ precision
Object detection system using YOLOv5 for rugby analysis. Developed a model with 90%+ precision that can identify key game elements including players, referees, scrums, rucks, and more in real-time (8.8ms per image).
🎮 Super Auto Pets AI - Reinforcement learning system with 1M+ training steps
Machine learning system for Super Auto Pets using reinforcement learning (PPO) and computer vision. Developed a coaching system that provides strategic recommendations based on game state analysis.
🌐 Vanderbilt Rugby Official Website – Team site built with Astro and TypeScript
Official team website built with Astro framework and TypeScript featuring responsive design, team roster management, match schedules, and media galleries. Implemented modern web development practices with component-based architecture and optimized performance.