The parabolic Anderson model (PAM), which is the Cauchy problem for the heat equation with random potential. The PAM is a mathematical model that describes how mass (i.e. matter or energy) flows in a medium in the presence of a field of sources and sinks.

One of the major limitations in culturing complex tissues or organs is the lack of vascularization in the cultured tissue. Development of a functional capillary bed could overcome this problem.

Promotor: Prof.dr.ir. E. Deprettere

Promotor: Prof.dr. A. Doelman, Co-promotor: V. Rottschäfer

Promoter: Ed F. Deprettere, Co-promoter: Todor P. Stefanov

Promotores: S.J. Edixhoven, P.Parent

Promotor: Prof.dr. S.F. Portegies Zwart

Radiography is an important technique to inspect objects, with applications in airports and hospitals. X-ray imaging is also essential in industry, for instance in food safety checks for the presence of foreign objects.

Promotor: Prof.dr. K.J. Batenburg

In deep reinforcement learning, searching and learning techniques are two important components. They can be used independently and in combination to deal with different problems in AI, and have achieved impressive results in game playing and robotics. These results have inspired research into artificial…

Promotor: M.T.M. Koper, Co-Promotor: L.B.F. Juurlink

Automated Machine Learning (AutoML) is widely used to automatically build a suitable practical Machine Learning (ML) model for an arbitrary real-world problem, reducing the effort of practitioners in the ML development cycle for real-world applications. Optimization is a key part of a typical AutoML…

In this thesis, topics relating to the optimization of high-throughput pipelines used for imaging are discussed. In particular, different levels of implementation, i.e., conceptual, software, and hardware, are discussed and the thesis outlines how advances on each level need to be made to make gains…

Peter Hoppenbrouwers

The endocannabinoid receptors CB1R and CB2R are involved in a plethora of processes, and consequently are involved in many pathological conditions. Their wide distribution makes the CBRs both an interesting therapeutic target and hard to study.

Dissociative chemisorption is an important reaction step in many catalytic reactions.

The thesis describes experimental steps towards reduction of friction on the macroscopic scale by scenarios of thermo- and superlubricity well-known on the nanoscale.

Optimization tasks in practice have multifaceted challenges as they are often black box, subject to multiple equality and inequality constraints and expensive to evaluate.

We present an extensive study of methods for exactly solving stochastic constraint (optimisation) problems (SCPs) in network analysis. These problems are prevalent in science, governance and industry.

Building a Deep Cross-media Transfer Network to extract visual relations that relieve the problem of insufficient training data for visual tasks.

Principles of Environmental Sciences provides a comprehensive picture of the principles, concepts and methods that are applicable to problems originating from the interaction between the living and non-living environment and mankind. Both the analysis of such problems and the way solutions to environmental…

Constraint multi-objective optimization with a limited budget for function evaluations is challenging. This thesis tackles this problem by proposing new optimization algorithms. These algorithms are applied on holistic ship design problems. This helps naval architects balance objectives like cost, efficiency,…

The focus throughout this thesis will be on gathering fundamental studies of the detailed structure and composition of the electrode/electrolyte interface effect on the rate and mechanism of key electrocatalytic reactions.

Can we provide the Dutch government with an integrative framework, wherein the various policies can be placed and the need for further measures can be identified?

This thesis applies data mining in commercial settings in the telecommunications industry.

Promotor: Prof.dr. W.T.F. den Hollander

A critical look at the impact assessment modelling of metals in Life Cycle Impact Assessment and improvement options.

Quantum annealing belongs to a family of quantum optimization algorithms designed to solve combinatorial optimization problems using programmable quantum hardware. In this thesis, various methods are developed and tested to understand how to formulate combinatorial optimization problems for quantum…

In this thesis, we show how MRFM can usefully contribute to the field of condensed-matter.

The LOFAR radio telescope produces petabytes of data every year. Radio Astronomers use complex multi-step pipelines to process this data and produce scientific images.

During the course of drug discovery translational steps are made.

Industrial manufacturing processes, such as the production of steel or the stamping of car body parts, are complex semi-batch processes with many process steps, machine parameters and quality indicators.

Promotor: Roeland M.H. Merks

CMLCA is a software tool that supports the technical steps of the Life Cycle Assessment. The focus of the program is on advanced computational aspects of life cycle inventory calculations.

For each living organism health is ensured by correct functioning of its cells. Cells therefore have elaborate methods for regulation of their proteins.

This thesis seeks to combine two different research topics; Multi-Objective Optimization and Complex Network Analysis.

Machine Learning is becoming a more and more substantial technology for industry.

In this thesis we explore machine and deep learning approaches that address keychallenges in high dimensional problem areas and also in improving accuracy in wellknown problems. In high dimensional contexts, we have focused on computational fluid dynamics (CFD) simulations.

The thesis introduces three methods for high-dimensional prediction problems in the biomedical field. The methods make use of empirical and variational Bayes in the estimation.

Promotor: K.E. Schalm, Co-promotor: S.S. Lee

Promotor: R.D. Gill, F. Taroni

This thesis investigates the contribution of quantum computers to machine learning, a field called Quantum Machine Learning. Quantum Machine Learning promises innovative perspectives and methods for solving complex problems in machine learning, leveraging the unique capabilities of quantum computers…

Promotor: R. Tijdeman, Co-promotor: H.J.J. te Riele

Als kennisinstellingen, gemeente, burgers en andere partijen of organisaties elkaar onvoldoende weten te vinden, komt kennis niet voldoende ten goede aan de samenleving. Het Leiden Healthy Society Center heeft de ambitie om kennis, beleid en praktijk duurzaam met elkaar te verbinden. Zo willen we onderwijs…

In this thesis we will explore the use of fuzzy systems theory for applications in bioinformatics.

In design optimization problems, engineers typically handcraft design representations based on personal expertise, which leaves a fingerprint of the user experience in the optimization data. Thus, learning this notion of experience as transferrable design features has potential to improve the performance…

1. To what extent do metallic NPs added to soil extractions change the activity, abundance, or community composition of microbes? 2. How do the effects of metallic NPs on soil microbes differ from the effects of the ions shedding from corresponding NPs?