This project aims to improve understanding of, and responses to, the phenomenon of lone actors through analysis of comprehensive data on cases from across Europe.

Transport inspectorates are looking for novel methods to identify dangerous behavior, ultimately to reduce risks associated to the movements of people and goods. We explore a data-driven approach to arrive at smart inspections of vehicles.

How does the cluster bootstrap procedure in combination with various types of linear models perform in the analysis of longitudinal data, compared to other methods.

The chemical and structural heterogeneity of toxoid vaccines makes their analysis challenging. However, detailed insights on a molecular level can be obtained by mass spectrometry.

How do secondary school teachers’ professional learning preferences relate to teaching experience and the school context?

We have studied shape with a particular focus on the zebrafish model system. The shape is an essential appearance of the phenotype of a biological specimen and it can be used to read out a current state or response or to study gene expression.

Thanks to data science, we can chart and search enormous quantities of related information. This generates all kinds of new insights, for example in complex global financial structures or such societal problems as loneliness.

In what way can teachers support and enlarge student engagement in a blended learning context?

The objective is to develop in vitro antigen degradation assays in order to mimic the fate of the antigen in vivo.

Doctoral Thesis

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This thesis addresses the challenge of sustainable urban development by analyzing the interplay between green and grey infrastructure to optimize resource use and ecosystem services.

Can we develop a generic method for Quan/Qual analysis of small molecule drugs, their metabolites and endogenous metabolites in (pre-)clinical samples?

Promotors: W. Jiskoot; G.J. Witkamp, Co-promotor: M.R. Nejadnik

D2.2 comprises the in-depth legal analysis of the initial heuristic model, focused on addressing, in more detail, the main legal concerns for data reusers in the European data economy. This detailed analysis of the legal propositions presented in D2.1 is supplemented by an analysis of the technological,…

D1.2 reports on the findings of an analysis of framework conditions relevant in the context of the data economy from a legal, a socio-economic and a technological perspective. The analysis is a key foundation for the creation of an initial, heuristic model of the European data economy. The deliverable…

In this dissertation (titled: Exploring the Synergies between Transfer in Reinforcement Learning and Procedural Content Generation) we explore how the two research fields named in the title, namely Transfer in Reinforcement Learning (TRL) and Procedural Content Generation (PCG) can synergize togethe…

A research goal for ABS is to develop miniaturized platforms for research in (stem)cell, in-vitro systems and application in clinical and preventive research. Combined with the high throughput, this development will make it possible to study the dynamics of pathogenesis in human and cellular models…

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

How can pre-Islamic poetry be used as a source to reconstruct the history of central Arabia at the dawn of Islam?

Promotor: S.M. Verduyn Lunel

Music profession requires strong reflective, collaborative, creative and improvisational skills, yet prevailing one-to-one tuition in conservatoire education focuses mainly on transmission of craft skills. Examining effects of students' collaborative and experiential learning, as in learning labs, creates…

Molecular complexes can be used as electrocatalysts for oxygen reduction, water oxidation, and/or hydrogen peroxide production.

With the dramatic growth of the image data on the web, there is an increasing demand of the algorithms capable of understanding the visual information automatically.

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.

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Promotores: Arjen Doelman, Jens Rademacher, Max Rietkerk

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The aim of this study was to provide insight into how teachers in higher education can be supported in the design, implementation and evaluation of group assignments by developing a theoretical and evidence-based framework for the design of group assignments.

In this consortium CWTS (Leiden University) collaborates with two Swedish SMEs: Monocl AB and Recorded Future AB. Monocl AB delivers intuitive analysis software to Life Sciences professionals in support of strategic decisions and improvement of business performance. Recorded Future AB is an organization…

This thesis mainly focuses on multimodal understanding and Visual Question Answering (VQA) via deep learning methods. For technical contributions, this thesis first focuses on improving multimodal fusion schemes via multi-stage vision-language interactions.

Computers are capable of making incredibly accurate predictions on the basis of machine learning. In other words, these computers can learn without intervention once they have been pre-programmed by humans. At LIACS, we explore and push the borders of what a revolutionary new generation of algorithms…

In 2018, the number of mobile phone users will reach about 4.9 billion. Assuming an average of 5 photos taken per day using the built-in cameras would result in about 9 trillion photos annually.

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The aim of this thesis was to examine what teachers want to learn themselves. The main research question was: what, how and why teachers want to learn? And does this depend on their years of teaching experience and the school at which they work?

Learning from small data sets in machine learning is a crucial challenge, especially when dealing with data imbalances and anomaly detection. This thesis delves into the challenges and methodologies of learning from small datasets in machine learning, with a particular focus on addressing data imbalances…

The purpose of this study was to investigate the formation and growth kinetics of complexes between proteins and oppositely charged polyelectrolytes.

This thesis mainly focuses on cross-modal retrieval and single-modal image retrieval via deep learning methods, i.e. by using deep convolutional neural networks.

Promotores: W.T. de Groot, M. Tchuenté, Co-promotor: J.P. Cheylan

In this article, Marco Cinelli, assistant professor at Leiden University College The Hague, examines proper and improper uses of Multiple Criteria Decision Analysis (MCDA) methods in energy systems analysis.

Exploring the value of data-driven approaches in education: collecting, analysing, and interpreting data from educational environments to improve teaching and learning outcomes.