Promotors: Prof.dr. T.H.W. Bäck, Prof.dr. B. Sendhoff (Technische Universität Darmstadt)

Promotor: H.J. van den Herik, B.R. Katzy, Co-promotor: K. Sailer

Lezing

The invention of neural networks marks a critical milestone in the pursuit of true artificial intelligence. Despite their impressive performance on various tasks, these networks face limitations in learning efficiently as they are often trained from scratch.

Promotor: Prof.dr. T.H.W. Bäck

Continuous optimization is never easy: the exact solution is always a luxury demand and the theory of it is not always analytical and elegant.

We strive to address the challenge of constructing a modeling language to write software which can take advantage of recent hardware developments (multicore, cloud) without compromising in its abstraction levels.

Modeling and analysis of cyber-physical systems are still challenging. One reason is that cyber-physical systems involve many different parts (cyber or physical), of different nature (discrete or continuous), and in constant interaction via sensing and actuating.

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.

This thesis investigates how quantum, quantum-inspired, and hybrid quantum-classical computation can enhance key points of the automated machine learning (AutoML) pipeline under the constraints of noisy intermediate-scale quantum (NISQ) devices.

Promotor: F.S. de Boer Co-promotor: P. T. de Gouw

Promotores: Prof.dr. J.N. Kok, Prof.dr. C.A. Mandemakers, Co-Promotor: G. Bloothooft

Promotor: J.N. Kok, Co-Promotor: A.J. Knobbe

Humans can see the world through the eyes of other humans and imagine what they know, want, and intend. This competence is known as Theory of Mind.

In this thesis it is posed that the central object of preference discovery is a co-creative process in which the Other can be represented by a machine. It explores efficient methods to enhance introverted intuition using extraverted intuition's communication lines.

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

Real-life processes are characterized by dynamics involving time. Examples are walking, sleeping, disease progress in medical treatment, and events in a workflow.

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: Prof.dr. E. Deprettere

Promotores: T.H.W. Bäck, Y. Tan, Co-promotor: M.T.M. Emmerich

Systems are called real-time systems, if the correctness of the system does not only depend on the correctness of the system output but also on whether the output is delivered on time.

Promotor: Prof.dr. B.R. Katzy, Prof.dr. H.J. van den Herik, Prof.dr. G.H. Baltes (University of Applied Sciences Konstanz)

Business Process Model and Notation (BPMN) has become the standard for business processes diagrams.

Prematurely born neonates require, amongst others, pharmaceutical therapy. Dosing guidelines for these therapies are often based on data from term born neonates or older infants, while these are not necessarily similar to prematurely born neonates.

Mining time series is a machine learning subfield that focuses on a particular data structure, where variables are measured over (short or long) periods of time.

Promotor: Prof.dr. B.R. Katzy

SuperCode: Sustainability PER AI-driven CO-DEsign

Predictive maintenance (PdM) is a maintenance policy that uses the past, current, and prognosticated health condition of an asset to predict when timely maintenance should occur.

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

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

Promotor: F. Arbab

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

Anticipatie op de uitdagingen en voordelen die AI-ondersteunde beoordelingen met zich meebrengen voor de relatie tussen studenten en docenten, de menselijke, evenals sociaal-economische kosten en kansen die zij voor universiteiten creëren.

The increasing competition in the automotive industry requires the tailored, swift development of technologically sophisticated vehicles. Therefore, the computationally expensive state-of-the-art simulation technologies are combined with optimization algorithms. An example of a real-world optimization…

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,…

Promotor: J.N. Kok, Co-promotor: C.M. Soares, A.J. Knobbe

Promotor: Prof.dr. J.N. Kok, Co-promotor: A.J. Knobbe

This thesis addresses the problem of designing performance and energy efficient embedded streaming systems, that is, systems which process a stream of input data coming from the environment and generate a stream of output data going into the environment.

Dit project ontwikkelt een wetenschappelijke methode om klinisch relevante nieuwe informatie te extraheren uit patiëntenforum-websites die ervaringen van patiënten bespreken over bv. medicatie, voeding, co-morbiditeiten, genetische factoren enz.

Innovation plays an essential role in firms' competitiveness and long-term success. It varies from different types, ranging from run-of-the-mill innovation that brings incremental changes to existing technologies to radical innovation that breaks from existing trajectories.

The marine shipping industry is one of the strongest emitters of nitrogen oxides (NOx), a pollutant detrimental to ecology and human health. Over the last 20 years, the pollution produced by power plants, the industry sector, and cars has been decreasing.

Promotores: J.N. Kok, H.J. Hoogeboom

Promotor: J.N. Kok, P.E. Slagboom Co-promotor: J.F.J. Laros

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: Prof.dr.ir. E. Deprettere

De Universiteit Leiden heeft onderzoeksinstituten gevestigd in Leiden en Den Haag.

In this PhD-thesis several new and existing data science application are described that are particularly focused on applications for tax administrations.

In dit project gebruiken we sociale netwerkanalyse om het gedrag van gebruikers op online fora en bijbehorende marktplaatsen in de tijd te analyseren.