PhD defence

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…

The European Space Agency (ESA) has published an interim data release from Gaia, the space telescope mapping out the Milky Way in 3D. The first scientific papers published today reveal half a million stars in the Omega Centauri globular cluster, nearly 400 candidate gravitational lensers and the positions…

Professor Frank den Hollander has been awarded a 10-year grant through the NWO Gravitation program, jointly with colleagues from the University of Amsterdam, the Center for Mathematics and Computer Science in Amsterdam, and the Technical University of Eindhoven.

The Reinforcement Learning lab conducts research into Reinforcement Learning and Intelligent Combinatorial Algorithms.

The programme is also offered in a blended learning version: this is a combination of distance learning and face-to-face learning. Read more information

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…

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?

The aim of this research project was to increase understanding of which collaborative learning approaches already exist in conservatoire education, and how implementation of collaborative learning could be supported.

Language learners in higher education increasingly conduct out-of-class self-directed learning facilitated by mobile technology. This project aims to explore how university students use mobile technology for their self-directed language learning and investigate factors that influence their self-directed…

In what way can teachers support and enlarge student engagement in a blended learning context?

Bringing together chemists and physicists to thoroughly investigate how electrochemical processes work on the smallest scale. That is the goal of the new Advanced Nano-electrochemistry Institute of the Netherlands, or ANION for short. The consortium receives a Gravitation funding of 23.6 million euros…

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

Automated Machine Learning (AutoML) is widely used to automatically build a suitable practical Machine Learning (ML) model for an arbitrary real-world problem, reducing the effort of practitioners in the ML development cycle for real-world applications. Optimization is a key part of a typical AutoML…

Three major cosmology-focused missions are planned for the next decade: the Euclid space telescope, the Vera C. Rubin Observatory in Chile, and the Nancy Grace Roman Space Telescope.

After this course

Learning from small data sets in machine learning is a crucial challenge, especially when dealing with data imbalances and anomaly detection. This thesis delves into the challenges and methodologies of learning from small datasets in machine learning, with a particular focus on addressing data imbalances…

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.

How do museum visitors interpret the authenticity of museum objects? How can we support visitors' meaningful interactions with real objects?

The active learning ambition is based on the idea that knowledge is more likely to ‘stick’ when students are actively engaged with their learning and research. This active student participation has implications for how we teach: less consumption of knowledge and more efficient use of contact hours.

The ambition to have flexible learning pathways is about creating possibilities to improve the content and form of students’ learning process, and to link learning to students’ needs. Students who have access to a flexible range of learning pathways can align their university career with their own personal…

Sewer pipes are an essential infrastructure in modern society and their proper operation is important for public health. To keep sewer pipes operational as much as possible, periodical inspections for defects are performed.

The Centre for Professional Learning (CPL) develops in-depth and challenging programmes for higher educated professionals.

The language learning resource centre unites all language teaching professionals working at Leiden University: teachers and researchers at the LUCL, ATC, LUCAS, LIAS, and ICLON.

Would you like to develop further and be challenged academically in your field or beyond? The Faculty of Humanities offers a wide range of courses to boost your career, learn new skills or broaden your knowledge.

All the data stored and processed by our computers is encoded as sequences of zeros and ones, called bits. Quantum computers offer an alternative to this traditional way of encoding and manipulating information.

LLInC supports innovative and high-quality education both within Leiden University and in partnership with academic and social organisations.

In deep reinforcement learning, searching and learning techniques are two important components. They can be used independently and in combination to deal with different problems in AI, and have achieved impressive results in game playing and robotics. These results have inspired research into artificial…

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.

Reinforcement learning is a framework that enables agents to learn in a manner similar to humans, i.e. through trial and error. Ideally, we would like to train a generalist agent capable of performing multiple tasks and achieving various goals.

This dissertation is about Bayesian learning from data. How can humans and computers learn from data?

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This dissertation aims to explore how university students use mobile technology for their self-directed language learning and investigate factors influencing their self-directed learning with mobile technology.

Exploring the value of data-driven approaches in education: collecting, analysing, and interpreting data from educational environments to improve teaching and learning outcomes.

Assessing Learning in Higher Education addresses what is probably the most time-consuming part of the work of staff in higher education, and something to the complexity of which many of the recent developments in higher education have added. Getting assessment ‘right’– that is, designing and implementing…

This thesis investigates how quantum, quantum-inspired, and hybrid quantum-classical computation can enhance key points of the automated machine learning (AutoML) pipeline under the constraints of noisy intermediate-scale quantum (NISQ) devices.

The ‘Leer te Durven!’ program (Learn to Dare) is a preventive training program for children with mild anxiety symptoms (Simon & Bögels, 2014). The program has been developed for children between the ages of 8 and 12 who feel or behave anxiously, avoid situations, are afraid of doing things wrong, appear…

Songbirds as vocal learners learn their songs and song preference from social tutors⁠. Tutor choice for both song and preference learning are important to characterize for understanding individual learning performance and cultural transmission of song⁠.