The focus of this thesis is on the technical methods which help promote the movement towards Trustworthy AI, specifically within the Inspectorate of the Netherlands.The goal is develop and assess... Show moreThe focus of this thesis is on the technical methods which help promote the movement towards Trustworthy AI, specifically within the Inspectorate of the Netherlands.The goal is develop and assess the technical methods which are required to shift the actions of the Inspectorate to a data-driven paradigm, concretely under a supervised classification framework of machine learning.The aspect of reliability is addressed as a data quality concern, viz. missingness and noise.The aspect of fairness is addressed as a counter to bias in the selection process of inspections.The conclusion is that, whilst no complete solution has yet been suggested, it is possible to address the concerns related to data quality and data bias, culminating in well-performing classification models which are reliable and fair. Show less
This thesis described the development of novel scanning tunneling microscopy techniques to investigate strongly correlated electronic states in quantum matter.
Real-world (black-box) optimization problems often involve various types of uncertainties and noise emerging in different parts of the optimization problem. When this is not accounted for,... Show moreReal-world (black-box) optimization problems often involve various types of uncertainties and noise emerging in different parts of the optimization problem. When this is not accounted for, optimization may fail or may yield solutions that are optimal in the classical strict notion of optimality, but fail in practice. Robust optimization is the practice of optimization that actively accounts for uncertainties and/or noise. Evolutionary Algorithms form a class of optimization algorithms that use the principle of evolution to find good solutions to optimization problems. Because uncertainty and noise are indispensable parts of nature, this class of optimization algorithms seems to be a logical choice for robust optimization scenarios. This thesis provides a clear definition of the term robust optimization and a comparison and practical guidelines on how Evolution Strategies, a subclass of Evolutionary Algorithms for real-parameter optimization problems, should be adapted for such scenarios. Show less
The theoretical foundation for the work reported here is provided by Landauer's scattering theory of electron transport. The three main ingredients of a scattering problem are (1) a set of... Show moreThe theoretical foundation for the work reported here is provided by Landauer's scattering theory of electron transport. The three main ingredients of a scattering problem are (1) a set of reservoirs that emit and absorb particles, (2) the particles themselves, that propagate as waves between the reservoirs and (3) a scatterer that obstructs free propagation. In this thesis two classes of problems are considered. The first class results when the physical quantities characterizing the reservoirs or the scatterer are not constant in time. The second class results when wave propagation is described by the Dirac equation rather than the Schroedinger equation, as is the case in a 2D form of carbon, called graphene. Show less
