Program Overview
The AI Engineering program at Carnegie Mellon University combines rigorous theoretical foundations with practical engineering skills. The curriculum focuses on building production-ready AI systems that solve real-world problems.
Coursework
- Multi-Agent Reinforcement Learning
- Deep Learning Systems
- AI Safety and Alignment
- Natural Language Processing
- Computer Vision
- Machine Learning Engineering
Research
Working on research projects in multi-agent systems and AI safety, exploring how large language models can be integrated with traditional planning algorithms to create more robust and interpretable AI systems.
Key Projects
- Safe AI Lab: Multi-agent coordination with safety guarantees
- LLM Path Planning: Integration of language models for navigation
- AI Safety Research: Verification methods for autonomous systems
Skills Developed
- Advanced PyTorch and TensorFlow implementations
- Distributed training and scaling
- Research methodology and technical writing
- System design for ML applications