Industrial manufacturing processes, such as the production of steel or the stamping of car body parts, are complex semi-batch processes with many process steps, machine parameters and quality indicators.

The Data-Driven Drug Discovery Network (D4N) is an initiative by researchers from Leiden University and collaborators to join efforts in applying and developing novel techniques from data science to drug discovery and related topics from bioinformatics.

Netherlands Statistics (CBS), Leiden University and the University of Amsterdam have started a collaboration in the form of a research project titled 'Enriching official economic statistics using data-driven modelling techniques'.

On 7 February 2019, Helena Ursic-Vrabec defended her thesis 'Uncontrollable: Data subject rights and the data- driven economy'. The doctoral research was supervised by Prof. dr. S. van der Hof.

Leiden University and the Ministry of Infrastructure and Water Management are involved in a collaboration in the form of a research project titled 'Data-Driven Risk Assessment in Infrastructure Networks'.

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.

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

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

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

More collaboration, combining data and asking the right questions. These are a few of the recommendations that policymakers and researchers formulated at the conference 'Data gedreven Beleidsontwikkeling' on 28 November 2017.

It is becoming increasingly common to collect data from children and young people through digital means. The impact of this so-called ‘dataveillance’ on children, who are monitored from birth via smartphones and Fitbits, is great.

With the conference circuit slowly reopening after Covid forced almost all academic interactions online, thousands of conference attendees descended on Brussels for Europe’s largest technology conference. eLaw’s annual sponsorship of one of the many CPDP conference panels brought a diverse range of…

Conference

Promotor: C. W. J. Beenakker, Co-promotor: J. K. Asboth

Edward Elgar

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…

Lecture

PhD defence

Science

Sarah Giest and Annemarie Samuels, both Assistant Professors at Leiden University, researched the quality and coverage of the data being collected for policiymakers to be used, specifically pertaining to minority groups.

Read-Urban was a first project to investigate whether policy recommendations can be made with the aid of linked data collections and data science and to gain experience with the success factors for such a process.

The key characteristic of active matter is the motion of an emergent collection (such as a flock of birds), which is driven by the consumption of energy by its active components (i.e. individual birds).

LIACS is a partner in the EU Erasmus+ Curriculum Development for the Asian education system. The knowledge available in the field of Data Science and Artificial Intelligence education will be shared and adapted for the Asian market.

Science

The studies presented in the work show the potential of the integrative use of biophysical data in defining the structural basis of protein interactions.

PhD defence

PhD defence

The role of material production as a driver of environmental impacts is increasing, which calls for a better understanding of global material flows. This thesis explores the role of in-use stocks of products, buildings and infrastructure as a key driver of global material demand and discusses the implications…

By comparing individual health data with population data, doctors can provide personalized health advice and patients can learn from each other's experiences. Wessel Kraaij, professor of Applied Data Analytics shows how personal data can have predictive value.

Data reuse and big data: a taxonomy for personal data reuse.

Data Sets Department of Economics

Modern computer-aided simulation tools used by various industries produce gigabytes of data. But currently, they take days and even up to weeks of computation effort. To make the best use of all these data, the DAMIOSO project focuses on developing algorithms and tools for managing, mining, and optimizing…

Promotores: Prof.dr. T.H.W. Bäck, Prof.dr. M.R.V. Chaudron, Co-Promotor: M.T.M. Emmerich

e-SIDES (ethical and societal impact of data sciences) is a Coordination & Support Action (CSA) part of the Horizon 2020 programme.

The extensive use of electronic communication channels and other devices has opened new possibilities for collecting data on human behavior. This information is sometimes openly accessible, but largely part of administrative registration systems that are not open to the broader public. The data provides…

The research programme Statistical Science is concerned with the analysis and interpretation of masses of data, the quantification of uncertainty using probability models, and the development and benchmarking of algorithms and methods with these aims.

The SAPPAO project aims to optimise the accuracy and reliability of predicting scheduled flight times. The full name of the project is 'A Systems Approach towards Data Mining and Prediction in Airlines Operations'.

The change from a closed institution to an open living environment for patients with late stages of dementia will give the patients more freedom in their day-to-day life. The effect of this change on the patients’ mobility, activity and interaction with others will be assessed with sensor technology…

The majority of scientists, from archaeologists through to zoologists, collect huge volumes of data. Their massive databases contain large amounts of information which is difficult for humans to filter. With a solid grounding in statistics, we can develop algorithms for analysing and identifying patterns…

The ability to collect and interpret huge quantities of data has become indispensable to society and academia. Leiden University is a knowledge and expertise centre for data science that places the emphasis on interdisciplinary collaboration and innovation.

LACDR adheres to strict data management rules, with the aim to make our data findable, accessible, interoperable and re-usable. For this reason all LACDR PhD candidates are required to prepare a data management plan and to implement data management rules accordingly. All PhD candidates follow a data…

The majority of scientists, from archaeologists through to zoologists, collect enormous volumes of data. Their massive databases contain large amounts of information which is difficult for humans to filter. With a solid grounding in statistics and computer science, we can develop algorithms for analyzing…

Today, everybody and everything produces data. People produce large amounts of data in social networks and in commercial transactions. Medical, corporate, and government databases continue to grow. Sensors continue to get cheaper and are increasingly connected, creating an Internet of Things, and generating…

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

What consequences does Brexit have for the protection of personal data?

Social and Behavioural Sciences

The project 'Data use, online consumer needs, business strategies and regulatory response' aims to explore and examine the factors that impact upon the efficacy of information disclosure duties pertaining to customer data use in online business.

Student and Educational Affairs, Centre for Innovation

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