Edward Elgar

Developing new medicines is one of modern science's most significant hurdles, a process marked by high costs, long timelines, and frequent failures of promising candidates.

If researchers make their data FAIR, computers can link large quantities of data and identify patterns, thus greatly accelerating the process of arriving at new insights. In Leiden, the birthplace of ‘FAIR data’, Professor Barend Mons explains the meaning of this term.

Health Data Science Leiden University

How can teachers be motivated by their students’ data in making stepwise changes to their teaching practices?

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‘Tell me something I don’t know,’ said skating coach Jac Orie to Leiden data scientist Arno Knobbe. And he did. Knobbe and his colleagues now assist athletes in all kinds of ways with the help of data mining.

The focus of the Bachelor Data Science & Artificial Intelligence is on computer science, and its applications in Artificial Intelligence. You will receive a strong basis in mathematics, statistics and computer science, combined with advanced knowledge of machine learning, cognitive science, human-robot…

How can we make the information in handwritten historical research reports accessible and searchable? Data scientists at Leiden University are working with other universities on a method that will improve access to cultural heritage.

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.

Study information

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…

Are you curious about how science and technology contribute to a sustainable and innovative future? At Leiden University, you’ll explore the world of data, natural laws and living systems. From mathematics to artificial intelligence, from climate challenges to high-tech innovation: you’ll learn to analyse…

This thesis investigates how the assessment of circular economy (CE) at the macro-economic level can be facilitated and promoted⁠.

Are you curious about how science and technology contribute to a sustainable and innovative future? At Leiden University, you’ll explore the world of data, natural laws and living systems. From mathematics to artificial intelligence, from climate challenges to high-tech innovation: you’ll learn to analyse…

In this thesis we explore machine and deep learning approaches that address keychallenges in high dimensional problem areas and also in improving accuracy in wellknown problems. In high dimensional contexts, we have focused on computational fluid dynamics (CFD) simulations.

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

On 12 September 2019, Michiel Rhoen defended his thesis 'Big Data, Big Risks, Big Power Shifts: Evaluating the General Data Protection Regulation as an instrument of risk control and power redistribution in the context of big data'. The doctoral research was supervised by Prof. G.J. Zwenne and Prof.…

There are around 300,000 people in the Netherlands who donate blood on a regular basis. Women can give blood up to three times a year and men up to five times, resulting in approximately one million blood donations each year. Patients that receive this donated blood are already in a vulnerable condition,…

Are you curious about how science and technology contribute to a sustainable and innovative future? At Leiden University, you’ll explore the world of data, natural laws and living systems. From mathematics to artificial intelligence, from climate challenges to high-tech innovation: you’ll learn to analyse…

Are you curious about how science and technology contribute to a sustainable and innovative future? At Leiden University, you’ll explore the world of data, natural laws and living systems. From mathematics to artificial intelligence, from climate challenges to high-tech innovation: you’ll learn to analyse…

Tools and Data of the department of Environmental Biology

On 21 November 2018, Lieke Kools defended her thesis 'Essays on wealth, health, and data collection'. The doctoral research was supervised by Prof. dr. K.P. Goudswaard en Prof. dr. C.L.J. Caminada.

Promotor: J.N. Kok, Co-promotor: W.A. Kosters

Although the General Data Protection Regulation (GDPR) harmonizes the protection of personal data across the EU as of May 2018, its open norms in combination with cultural differences between countries result in differences in the practical implementation, interpretation and enforcement of personal…

Explaining treatment response variability between and within patients can support treatment and dosing optimization, to improve treatment of individual patients.

DIGIFOOD is a transnational research project that investigates how data governance can support equitable and sustainable digital food systems. Around the world, digital technologies are transforming agriculture. Sensors in soil, satellites in space, and mobile phones in farmers’ hands are generating…

The Collective Experience of Empathic Data Systems (CEEDs) consortium developed novel integrated technologies that support experiencing, analysing and understanding of very large datasets.

This dissertation focuses on developing new mathematical and statistical methods to properly represent time-varying covariates and model them within the context of time-to-event analysis.

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.

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.

On 27 May, Dimitra Stefoudi defended the thesis 'Legal and policy aspects of space big data: legal implications of the use of large amounts of space data – regulatory solutions and policy recommendations'. The doctoral research was supervised by Steven Truxal and Bart Custers.

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Workshop

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Workshop

Understanding how data derived from wearable technology can be used to identify effective changes in behaviour that are likely to result in health improvements

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.

Data science is now growing fast in many places, but scholars at Leiden University have been developing data science techniques for a long time already. Thanks to their broad-based expertise, Leiden statisticians are currently combining the achievements in statistics with the latest methods of statistical…

Workshop

The use of increasingly large and diverse datasets to guide urban climate action has implications for how, and by whom, local governments are held accountable.

This project develops a scientific method to extract clinically relevant new information from patient forum websites that discuss patient experiences concerning e.g. medication, nutrition, co-morbidities, genetic factors etc.

ChEMBL is a large-scale drug discovery database containing bioactivity information primarily extracted from scientific literature.

Study information

This thesis deals with the use of sound in interactions in the context of participatory systems and data sonification. We investigate an interactive environment where participants perceive information of the data through sound elements.

Archiving Medieval and Post-Medieval Archaeological Fieldwork Data from the Eastern Mediterranean (600-2000)

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.

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.

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