AI for Engineering and Real-world Decision Making
Overview
Translating computational intelligence research into practical solutions for engineering optimization, intelligent control, and real-world decision-making.
Key Questions
- How can we bridge the gap between theoretical advances and real-world deployment?
- What are the key challenges in applying evolutionary computation to engineering problems with expensive evaluations?
- How can AI systems support human decision-making in complex engineering scenarios?
Our Contributions
- Applied dynamic optimization techniques to engineering control problems
- Developed surrogate-assisted approaches for expensive optimization
Open Problems
- Handling uncertainty and robustness in real-world optimization
- Human-in-the-loop optimization for engineering design
- Scalable optimization for industrial-scale problems
Prospective Student Projects
- Surrogate-assisted optimization for engineering design
- Robust optimization under uncertainty for real-world applications
- Multi-fidelity optimization for engineering systems