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.

The research in this dissertation aims to optimise blood donation processes in the framework of the Dutch national blood bank Sanquin. The primary health risk for blood donors is iron deficiency, which is evaluated based on donors' hemoglobin and ferritin levels.

Online data breaches are recurrent and damaging cyber incidents fors organizations worldwide. This study examines how organizations can effectively mitigate reputational damages in the aftermath of data breaches by hacking, through situational crisis communication strategies.

Webinar with Q&A

Promotor: P.D. Grünwald

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…

Als gevolg van de grote technologische vooruitgang in de gezondheidszorg worden in toenemende mate gegevens verzameld tijdens de uitvoering van klinische onderzoeken.

Big data promises to transform public decision-making for the better by making it more responsive to actual needs and policy effects. However, much recent work on big data in public decision-making assumes a rational view of decision-making, which has been much criticized in the public administration…

This project, commissioned by DG Research and Innovation, aims to provide information for policies that lead to the creation and improvement of the conditions which will allow researchers and European industries to safely master the properties of nanomaterials and to innovate with nanotechnology.

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…

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?

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

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…

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…

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.

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.

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

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.

The goal is to establish an intuitive search and querying service that allows researchers to quickly retrieve the most valuable digital resources, in order to allow them to integrate and synthesise the results into a coherent narrative of the past. The current focus of the project is to implement…

Latest technological developments in data mining and profiling.

Indigenous Latin American artifacts have attracted the interest of Europeans since the earliest moment of contact between Europeans and the Indigenous peoples of the Americas. The ERC-funded BECACO project uses an innovative multidisciplinary framework to investigate the provenance of ethnographic and…

What workflow of non-destructive techniques provides accurate, valuable data to improve our understanding of Caribbean archaeological landscapes? How were Amerindian settlements configured?

This article provides an in‐depth assessment of lone actor terrorists’ attack planning and preparation.

Parkinson's disease is the second most common neurodegenerative disease in the world. One of its symptoms is the loss of dopaminergic neurons in the substantia nigra pars compacta.

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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.

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…

D1.3 describes a set of five case studies relevant in the context of the EuDEco project. Case studies are considered relevant if they are initiatives focusing on the promotion of big data and data reuse or pilots facilitating data reuse in one form or the other. The case studies were expected to allow…

Sport Data Center

With the rise of information and communication technologies, large amounts of data are being generated and stored in databases. In order to get a better grip on these large amounts of data, serious efforts are being made to discover patterns and relations in the data with the help of new techniques.…

Quantifying physical activity (using accelerometers) and combining the frequency and intensity of activities with health data (brain MRI, traditional clinical parameters and metabolomics) is of utmost importance to monitor mobility and health among older individuals and study health promotion during…

The research of this PhD project can be subdivided into two main disease areas: migraine and stroke. For both we will be investigating how artificial intelligence (AI) and machine learning (ML) techniques can be used to study these afflictions, their (early) detection, and their potential treatment.

Quantum computers are a proposed fundamentally new type of computer. They aim to perform some computations much faster than previously possible by exploiting phenomena at the quantum scale, called superposition and entanglement.