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…

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…

This thesis applies data mining in commercial settings in the telecommunications industry.

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

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'.

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.

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

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

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

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

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. The network is embedded in the Leiden Centre of…

How can citizen science be used to communicate and provide data for social network analysis?

Using positional data to determine which tactics lead to a successful attack? Rens Meerhoff, researcher at the Sports Data Center of the Leiden Institute of Advanced Computer Science (LIACS), has been using data-mining to analyse football tactics for several years. In Friesch Dagblad he explains the…

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.

Pharmaceutical research should make more use of data science, says Gerard van Westen, postdoctoral fellow at the Leiden Academic Centre for Drug Research (LACDR). ‘If we want to have better drugs, we should start with data.’

‘Big data’ is currently a hot topic and it is extremely relevant for archaeology, as new digital methods and a data explosion are radically changing archaeological research. What exactly is big data and how can we apply new data science techniques in archaeology? This was the topic of the 19th LCDS…

Text and data mining: searching and analysing large quantities of texts, images or other data. On 29 February during a Knowledge Café in the Academy Building visitors discussed the question of why this method isn't being widely applied in Europe.

How are data science and statistics related? And what can data scientists learn from statisticians? These were the central questions of the 8th meeting of the Leiden Centre of Data Science (LCDS), which took place on Friday, November 13th. Recent developments in the field of statistics, including new…

PhD Defence

Data and information should be stored in a way that computers can understand, says Barend Mons, professor of Biosemantics at the Leiden University Medical Center and Chair of the High Level Expert Group for the European Open Science Cloud. We speak with him about FAIR data, knowlets and nanopublicat…

Conference

The Digital Archaeology research group manages two computer laboratories with different purposes: the teaching lab (F1.01) and the research lab (A1.13a).

Data science offers great opportunities for legal research, according to Simone van der Hof and Bart Custers (eLaw). But at the same time, we have to keep an eye on the unwanted side effects of big data - such as ethnic profiling.

Real-life processes are characterized by dynamics involving time. Examples are walking, sleeping, disease progress in medical treatment, and events in a workflow.

PhD Defence

The Digital Archaeology chairgroup is currently still involved in a project related to EDNA project (national data archive for archaeology). Although this time the focus on innovative research in Computer applications is much stronger. All the archaeological projects in the e-archive are documented…

Lecture, Seminar

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…

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

The master's specialisation Data Science: Computer Science at Leiden University provides students thorough knowledge and understanding of statistical and computational aspects of data analysis, including their application in databases, advances in data mining, networks, pattern recognition, and deep…

Dutch speedskaters have been winning the most medals in speed skating at the Winter Olympics for years. How? Based on their intuition. Scientist Jeroen van der Eb of the Data Mining & Sports group of the Leiden Institute of Advanced Computer Science (LIACS) wants speedskaters to adjust their irons based…

The Leiden Centre of Data Science (LCDS) is a network of researchers from different scientific disciplines, who use innovative methods to deal with large amounts of data.

The Astronomy and Data Science master’s specialisation at Leiden University combines advanced Astronomy courses with relevant courses from the Computer Science programme at Leiden University.

Mining time series is a machine learning subfield that focuses on a particular data structure, where variables are measured over (short or long) periods of time.

Promotor: J.N. Kok, Co-promotor: C.M. Soares, A.J. Knobbe

In the autumn of 2016, the Leiden Centre of Data Science (LCDS) organized a crash course Data Science for employees of the Ministry of Infrastructure and Environment (I&M). The certificates were awarded on January 24th, 2017.

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…

PUMA aims at composing a geological map of the urban mine of Amsterdam for a selection of metals. Where are main deposits of copper, iron and aluminium located, when will they become available for secondary production, in what state and shape are they?

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.

The Data Science for Statistical Science master’s specialisation at Leiden University gives you a better understanding of statistical models, especially in relation to Data Science, including their application and interpretation in a broad range of empirical research.

At the Sport Data Center, five research themes are explored.

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.