Making predictions about emotional problems or the effects of air pollution: Marjolein Fokkema’s algorithms are getting better at this all the time. She is making her algorithms increasingly flexible, so they can predict not just characteristics at one particular moment, but also how skills, for example,…

Artificial intelligence algorithms govern in subtle, yet fundamental ways, the way we live and are transforming our societies. The promise of efficient, low‐cost or ‘neutral’ solutions harnessing the potential of big data has led public bodies to adopt algorithmic systems in the provision of public…

Top scientists of three Dutch universities are working on software and systems for quantum computers. Researchers of the Leiden Institute of Advanced Computer Science (LIACS) and the Leiden Institute of Physics (LION) are developing new algorithms to make those super computers work. The coming years,…

Many important topics in computer science, such as the correctness of software, the efficiency of algorithms and the modeling of complicated systems, depend on sound theoretical underpinnings. In the Theory group, we study these fundamental building blocks and develop verification methods to prove system…

Promotores: H.W. Lenstra, K. Belabas (University of Bordeaux)

Artificial intelligence could help make the work of public sector organisations, professionals, policy- and decision makers more effective, more efficient, and ideally could make it more rationalised and evidence-based.

In this thesis we present several methods to automate tomographic reconstruction algorithms and several novel tomographic reconstruction algorithms with the focus on being easily applicable and efficient to use.

Big data promises to transform public decision-making for the better by making it more responsive to actual needs and policy effects. However, much recent work on big data in public decision-making assumes a rational view of decision-making, which has been much criticized in the public administration…

This thesis covers several aspects of quantum algorithms for near-term quantum computers and its applications to quantum chemistry and material science.

The Algorithms and Software Technology (AST) research programme performs fundamental research in the areas of algorithm design and analysis.

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

Promotor: J.N. Kok, P.E. Slagboom Co-promotor: J.F.J. Laros

Promotor: Robert Tijdeman, Co-promotor: Cornelis Kraaikamp

Promotor: S.J. Edixhoven, Co-promotor: R.S. de Jong

Promotor: Prof.dr. J.P. Abrahams, Prof.dr. M. van Heel

Structural variants (SVs) are the hidden architecture of the human genome, and are critical for us to understand diseases, evolution, and so on.

Smart algorithms and powerful processors are just as essential for astronomy as big telescopes. Astronomers at Leiden University therefore constantly operate at the interface between astronomy and data science.

A growing global concern is that automated recognition systems may exacerbate and reinforce existing biases that different societies have with respect to gender, age, race, and sexual orientation. Questions around the consequences of automated gender recognition are particularly poorly understood and…

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

Quantum computing is an emerging technology, which holds the potential to simulate complex quantum systems beyond the reach of classical numerical methods.Despite recent formidable advancements in quantum hardware, constructing a quantum computer capable of performing useful calculations remains challenging.In…

Promotor: R. Tijdeman, Co-promotor: H.J.J. te Riele

The Automated Design and Analysis of Algorithms (ADA) research group pursues the development of Artificial Intelligence techniques that complement, rather than replace, human intelligence.

Inverse problems are problems where we want to estimate the values of certain parameters of a system given observations of the system. Such problems occur in several areas of science and engineering. Inverse problems are often ill-posed, which means that the observations of the system do not uniquely…

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…

Quantum hardware comes with a different computing paradigm and new ways to tackle applications. Much effort has to be put into understanding how to leverage this technology to give real-world advantages in areas of interest for industries such as combinatorial optimization or machine learning.

The focus of the Multicriteria Optimization and Decision Analysis (MODA) group is to develop foundations of methods in multi-objective optimization.

This thesis addresses questions on effectively using variational quantum circuits for machine learning tasks.

Born in Europe roughly 100 years ago, quantum physics brought forth a veritable technological revolution through semiconductors, lasers, fibre optics, and many other technologies that are today ubiquitous in our lives. Now, during the second quantum revolution, Europe can take the lead once more in…

Imagine how much time, money and discomfort it would save: a personalised treatment for each individual patient. Precision medicine like this is coming ever closer, thanks in part to Elise Dusseldorp’s algorithms. They retrieve a wealth of information from research data.

Social and Behavioural Sciences, Psychology

Science, Institute of Biology Leiden (IBL)

Multi-objective optimization is an effective technique for finding optimal solutions that balance several conflicting objectives. It has been applied in many fields of our world, because practical problems usually have more than one desired goal. For example, developing a new vehicle component might…

On 13 June 2024, the University of Tuscia (Viterbo, Italy) hosted a doctoral seminar in the series 'Law and Artificial Intelligence', organised by the PhD programme in 'Law of European and Global Markets. Crisis, Rights, Regulation' and coordinated by Professor Rosa Ruggiero.

Modern optimization algorithms offer solutions for architectural decisions like spatial, structural and energy efficiency. A young computer scientist from Leiden University co-authored a paper that won the Best Paper Award at a leading conference in Krakow during the summer.

Multi-objective evolutionary computation aims to find high quality (Pareto optimal) solutions that represent the trade-off between multiple objectives.

Continuous optimization is never easy: the exact solution is always a luxury demand and the theory of it is not always analytical and elegant.

Chapter by Fabio Cristiano and Emilio Distretti for the volume The Aesthetics and Politics of the Online Self, edited by Donatella Della Ratta, Geert Lovink, Teresa Numerico, and Peter Sarram for Palgrave Macmillan.

Lecture

Source: Nature Biotechnology, Volume 2014, Issue June (2014)

Research in Leiden University’s Institute of Political Science focuses on the dynamics and the interaction of political institutions, individual decision-making, and collective behaviour.

If an algorithm has to learn to understand language, simply having a lot of data doesn’t help much. Like us, a computer has to learn the language in interaction with others. Tessa Verhoef is fascinated by how this interaction works.

How do individuals make decisions? What determines the quality of group decisions? When and why do people cooperate with others? How does intergroup competition evolve?

In science, it is of vital importance that multiple studies corroborate the same result. Researchers therefore need to know all the details of previous experiments in order to implement the procedures as exactly as possible. However, this is becoming a major problem in neuroscience, as animal studies…

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

This article explores the concept of issue prioritisation within the context of public administration research, focusing on decision-making processes.

Efficiently responding to others’ emotions has great survival value, especially for social species, such as primates, who establish close, long-term bonds with group members. The closest living relatives to humans are the chimpanzee and the bonobo. Studying these species, and comparing them on the exact…