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

The results of the investigations by citizens are used in an innovative research project that investigates the potential of machine learning and automated detection in archaeology.

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

Computers are capable of making incredibly accurate predictions on the basis of machine learning. In other words, these computers can learn without intervention once they have been pre-programmed by humans. At LIACS, we explore and push the borders of what a revolutionary new generation of algorithms…

Computers are capable of making incredibly accurate predictions on the basis of machine learning. In other words, these computers can learn without intervention once they have been pre-programmed by humans. At LIACS, we explore and push the borders of what a revolutionary new generation of algorithms…

Promotor: Prof.dr. T. Hankemeier, Co-Promotores: T. Reijmers, L. Coulier

How to come to valid risk stratification of alcohol use disorder?

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…

CRANK is a novel suite for automated macromolecular structure solution and uses recently developed programs for substructure detection, refinement, and phasing.

Political institution (like the Council of the European Union and the European Parliament) generate large bodies of text. These great amounts of text can impossibly be read by a researcher. Contrary to human researchers, computers are able to read thousands of documents a day. In this research project…

Promotor: Prof.dr. T. Hankemeier, Co-promotor: Dr. Theo Reijmers

Lecture

Promotores: Prof.dr. J. Zaanen & Prof.dr. K.E. Schalm

‘We hope our paper highlights the possibilities and benefits of including artificial intelligence in quantum physics to do new discoveries.’ Vedran Dunjko of the Leiden Institute of Advanced Computer Science contributed to a paper that was published in PNAS last year and now received a Cozzarelli Prize…

By studying language you can reconstruct the history of different communities, even when no other historical sources, such as written documents, are available. In the coming years, researchers Willem Adelaar and Marian Klamer will be carrying out this kind of reconstruction in areas of great linguistic…

Legibility in the Age of Signs and Machines offers a compelling reflection on what the notion of legibility entails in a machinic world in which any form of cultural expression – from literary texts, films, artworks and museum exhibits to archives, laws, computer programs and algorithms – necessarily…

Promotor: J.P. Abrahams, Co-Promotor: N.S. Pannu

Cláudio de Sá predicted the preferences of people using rankings. He adjusted ‘classical’ machine learning approaches, making them suitable for predicting preferences. His work can be applied in the prediction of election results. PhD defence on 16 December.

Source: J Cheminform, Volume 6, Issue 1 (2014)

How do secondary school teachers’ professional learning preferences relate to teaching experience and the school context?

It is a common technique in global optimization with expensive black-box functions to learn a surrogate-model of the response function from past evaluations and use it to decide on the location of future evaluations.

In 2018, the number of mobile phone users will reach about 4.9 billion. Assuming an average of 5 photos taken per day using the built-in cameras would result in about 9 trillion photos annually.

Promotores: Prof.dr. J.N. Kok, Prof.dr. M.R.V. Chaudron, Co-Promotor: P. van der Putten

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With the dramatic growth of the image data on the web, there is an increasing demand of the algorithms capable of understanding the visual information automatically.

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Bright explosions appear all over the radio and gravitational-wave sky. This dynamic side of the universe which has just been discovered, can be mapped by self-learning machines. The National Science Agenda granted 5 million euro’s to CORTEX, the Center for Optimal, Real-Time Machine Studies of the…

The aim of this study was to provide insight into how teachers in higher education can be supported in the design, implementation and evaluation of group assignments by developing a theoretical and evidence-based framework for the design of group assignments.

Multidisciplinary research has established that VAT-results are in practice six times lower than what it should have been. The new estimates rely on machine learning techniques.

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.

The aim of this thesis was to examine what teachers want to learn themselves. The main research question was: what, how and why teachers want to learn? And does this depend on their years of teaching experience and the school at which they work?

Heightened activation of the striatum that adolescents show in response to reward is often associated with risk-taking and negative health consequences. This article in Nature Communications investigates a potential positive side of this heightened activation. It shows that the activity peak in late…

Blended learning is all about combining face-to-face instruction with online education.

Course

Inaugural Lecture

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'.

How is collaborative learning in teacher education designed and implemented? How do students experience those collaborative learning assignments? What aspects of the design and the implementation lead to which perceived learning outcomes?

In CCLS several subgroups have formed, below you can find an overview of these groups with the names of the leading researchers and a short outline of the project.

To what extent are university teachers' individual learning paths influenced by their teaching experience, motivation, and conceptions of teaching and learning through educational technology?

The active learning network joins together everyone interested in the subject to move the theme further within Leiden University. The SALTSWAT pilot program researches the ways forward for Leiden University.

Have you always wanted to use your own coffee mug at the university coffee machines but it was never accepted? We have good news for you!