The AI&ES program is structured around six key interdisciplinary tracks, allowing students to tailor their learning to specific industries:
- Control principles and machine learning for intelligent systems
- Engineering applications in mechatronics and embedded AI
- AI-driven smart transportation solutions
- Autonomous driving technologies
- Data science for traffic optimization
- AI applications in medical imaging and diagnostics
- Personalized healthcare solutions
- Machine learning for bioengineering
- Urban AI solutions for sustainability
- Data analytics for smart infrastructure
- AI in energy efficiency and environmental monitoring
- AI in fundamental scientific research
- Computational physics and AI-driven simulations
- Data-driven exploration in physics, chemistry, and beyond
- AI-powered industrial automation
- Data analytics for predictive maintenance
- Digital twin technology for smart manufacturing