Bayesian preferential many-objective optimization with imperfect knowledge

Computational efficient multiphysics-based topology design of high-performance electric machines employing additive manufacturing

Doctoral project Ivo Couckuyt

Bayesian Preferential Many-Objective Optimization with Imperfect Knowledge

Data-efficient generative models for innovative engineering design

Essays on Machine Learning: Advances in Forecasting and Optimization

Machine Learning for Accurate and Efficient Uncertainty Quantification in Radiological Waste Characterization

Bayesian Active Learning for Engineering Design and Optimization under Uncertainty

Bayesian Optimization for Engineering Design and Process Optimization

Data-Efficient Machine Learning for Making Interpretable Decisions

Data-Efficient Physics-Informed Machine Learning

Doctoral project Arun Kaintura

Doctoral project Hua Wei

Doctoral project Joachim van der Herten

Doctoral project Nicolas Knudde

Machine Learning with Radar Sensors for Smart Healthcare

Bayesian many-objective optimization with noise and user preference learning.

Data-efficient surrogate modeling for science and engineering

Development of surrogate-assisted algorithms for combined design and trajectory optimization of dynamic mechatronic systems

Generative design of linear passive electronic systems

Learning complex patterns with Gaussian processes

Versatile surrogate-based optimization of medium-scale and large-scale problems.