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

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.

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.

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.

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…

Sport Data Center

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

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.

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.

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

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…

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…

Athletes always strive for the top. How can data scientists assist them in improving their performance? During the seminar Data Science and Sports, the possibilities and challenges of collaboration between these two worlds were discussed.

By analysing the metabolism using big data techniques, we can identify health risks at an earlier stage. Thomas Hankemeier, professor of Analytical Biosciences at the Leiden Academic Centre for Drug Research, explains how that works.

Triplet superconductivity refers to a condensate of equal-spin Cooper pairs (pairs of electrons with equal spin).

Tuberculosis is a major global health problem caused by the Mycobacterium tuberculosis complex, claiming more than a million lives annually.

How does invasive hybridization affect threatened native species?

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.

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

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.

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…