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Overview
Applied AI, engineering decision support, and cross-cutting methodological work that sits outside the three core research directions.
Key Questions
- How can we bridge the gap between theoretical advances and real-world deployment?
- What are the key challenges in applying computational intelligence to engineering problems with expensive evaluations?
- How can AI systems support human decision-making in complex scenarios?
Our Contributions
- Applied dynamic optimization techniques to engineering control problems
- Developed surrogate-assisted approaches for expensive optimization
- Spanned applied work, methodological reflection, and cross-domain optimization problems
Recommended Papers
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