This project aims to explore and examine the factors that impact upon the efficacy of information disclosure duties pertaining to customer data use in online business.

Tomography is a powerful technique to non-destructively determine the interior structure of an object.Usually, a series of projection images (e.g.\ X-ray images) is acquired from a range of different positions.

How to access the end-of-supply risk of spare pares using big data analytics

Promotor: A.P.IJzerman Co-promotor: A. Bender

Due to the modern techniques of combinatorial chemistry and high-throughput screening, data on the biological activity of many millions of compounds is known. However, it is still very difficult to transfer this data into knowledge: if we know that compounds A and B bind to a certain protein with high…

Promotor: M.T.M. Koper, Co-promotor: L. Juurlink

The Role and Effectiveness of the G20. In this article, published in The Changing Global Order part of the United Nations University Series on Regionalism book series, author Jaroslaw Kantorowicz discusses the evolution of the G20.

What are the essential determinants of (dis)trust? And, what are the effects of being (dis)trusted?

On 23 April, Andreas Häuselmann defended the thesis 'EU privacy and data protection law applied to AI: unveiling the legal problems for individuals'. The doctoral research was supervised by Gerrit-Jan Zwenne and Bart Custers.

Promotor: B. vd Water, T. Schmidt, Co-Promotor: E.H.J. Danen

This monograph focuses on clustering of objects in high-dimensional data, given the restriction that the objects do not cluster on all the attributes, not even on a single subset of attributes, but often on different subsets of attributes in the data.

VODAN Africa started as a platform to enable access to critical data needed from Africa to fight the novel COVID-19. The initiative was inspired by the experience from the Liberia Ebola Virus outbreak in 2014: early detection requires contact tracing. Inclusion of the most vulnerable is critical to…

This thesis focuses on data found in the field of computational drug discovery. New insight can be obtained by applying machine learning in various ways and in a variety of domains. Two studies delved into the application of proteochemometrics (PCM), a machine learning technique that can be used to…

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

Promotor: J.N. Kok, Co-promotor: F.J. Verbeek

The aim of this project is to develop accurate but interpretable ensemble learning methods for high-dimensional multi-domain data.

To what extent is it possible to utilise traditional and new media data to examine and understand the nature and scope of homicide in Indonesia?

How public service motivation and professionalism affect decision-making in dilemma situations. Individuals who work in the public sector see themselves confronted with conflicting values, contradictory demands, and the need to serve an at times difficult to define ‘public interest’.

Promotor: Prof.dr. B.R. Katzy, Co-promotor: R. Ortt

This thesis describes the functional analysis of the Arabidopsis AHL15 gene.

Data play an important role in any organization. More and more data are available about products, about production processes and about customers. At the annual LIACS Business Event on Wednesday 18 January, the central message was how to find irregularities in Big Data, and how it can help you to track…

The deeper understanding of an organism's pathology is important for developing treatments. Over centuries of systematic research, clinical researchers have demonstrated that the more information they acquire about the cellular properties and their organisation in the tissue, the better they can understand…

Generally the data from remote sensing surveys - the scanning of the earth by satellite or aircraft in order to obtain information about it - is screened manually in archaeology. However, constant monitoring of the earth's surface causes a huge influx of data of high complexity and high quality. To…

This project aims to develop advanced data analysis methods for monitoring and increasing our understanding on biodiversity dynamics in nature reserves such as the Oostvaardersplassen.

Tremendous amounts of data are generated in scientific research each day. Most of this data has more potential than we are using now, says Katy Wolstencroft, assistant professor in bioinformatics and computer science. We just need to integrate and manage it better.

This project’s aim is to critically assess current homicide data sources in order to develop a proposal for long-term EU-level monitoring of DRH.

The RISIS project aims at creating a distributed research infrastructure to support and advance science and innovation studies. This will give the field a strong scientific push forward, and at the same time, provide a radically improved evidence base for research and innovation policies, for research…

Promotor: Prof.dr. J. Kuiper, Co-promotor: Saskia C.A. de Jager

Sport Data Center

Autopaghy is an intracellular degradation system which targets cytosolic components to lytic compartments for degradation and recycling of the building blocks of the cell.

While bioinformatics methods deal with the analysis of sequence information (be it proteins or DNA), the field of cheminformatics is concerned with the analysis of small-molecule datasets.

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.

Data science offers exciting new instruments for governments to reach out to citizens, for example by using data-driven information channels, providing real-time simulations, or personalizing services based on citizen data. At the same time, the possibilities and use of data science methods can have…

Time-series forecasting through modelling sequences of temporally dependent observations has many industrial and scientific applications. While machine learning models have been widely used to create time-series forecasting models, creating efficient and performant time-series forecasting models is…

This study seeks to partially fill the knowledge gap about national culture in Africa, basing its research on data on ethnolinguistic groups (instead of administrative regions).

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.