Scientific topics

Theoretical aspects and fundamentals

• Mathematical theory and formulation of inverse and optimization problems
• Neural meta-modelling
• Regularization techniques
• (Model) order reduction
• Identification problems
• Sensitivity analysis
• Design optimization

Algorithms

• Machine learning techniques for optimization and inverse problems
• Reconstruction techniques
• Deterministic, stochastic and hybrid techniques
• Multi-objective and multi-level optimization
• Heuristic approaches
• Design of experiments
• Constraint handling
• Robust optimization under uncertainty
• Objective functions and direct problems
• Algorithmic efficiency

Applications

• Optimal energy management
• Biomedical engineering
• Control systems
• Coupled problems
• Electrical machines
• Industrial and biomedical tomography
• Information and communication systems
• Large scale systems
• Mechatronics
• Micro- and nano-systems
• Non-destructive evaluation
• Sensors and actuators
• Smart applications
• Transportation and mobility
• High frequency and antenna design
• Benchmark problems

Software methodologies

• Parallel and distributed computing, GPU
• Soft computing and artificial intelligence