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…

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,…

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.

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

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

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…

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.

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: 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

For optimization problems, it is often unclear how to choose the most appropriate optimization algorithm. As such, rigorous benchmarking practices are critical to ensure we can gain as much insight into the strengths and weaknesses of these types of algorithms.

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

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

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

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…

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

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

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.

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…

This thesis surveys the intersection of computed tomography (CT) and machine learning (ML), treating CT as an ill-posed inverse problem shaped by object properties, imaging physics, and data limitations.

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.

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

In the era of big data, extracting insights from complex datasets is a key challenge. This thesis demonstrates the superiority of graph-based methods over traditional clustering (e.g., k-means, DBSCAN) and outlier detection for analyzing high-dimensional and noisy data.

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

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

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.

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,…

The increasing competition in the automotive industry requires the tailored, swift development of technologically sophisticated vehicles. Therefore, the computationally expensive state-of-the-art simulation technologies are combined with optimization algorithms. An example of a real-world optimization…

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.

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

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.

The main topic of this PhD thesis is the Arakelov ray class group of a number field, an algebraic object that contains both the ideal class group structure and the unit group structure.

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…

Assistant Professor Vedran Dunjko and his team received a gift from Google to support their quantum research. The research focuses on whether quantum computers can provide new ways of understanding the mysteries of high-energy physics.

How can computers help design optimal buildings? PhD student Koen van der Blom makes algorithms that take into account all kinds of different architectural requirements, in order to reach the best compromise. And that is quite difficult: 'Algorithms do not automatically understand that a building that…

Every day we make use of devices, services and apps which contain algorithms that could be discriminating. These range from Facebook to self-driving cars, from the Tax Authorities to a rotating door.

The Leiden team

Addressing the core novel objective of scalably assessing the impact of possible interventions through counterfactual prediction based on spatio-temporal data.

Using biologically inspired algorithms on 'edge devices', such as cameras and mobile phones, is what Svetlana Minakova's PhD research was all about. She conducted research on Convolutional Neural Networks(CNN). Making these algorithms work in different situations is a complicated task. 'Most design…

Every day we make use of devices, services and apps which contain algorithms that could be discriminating. These range from Facebook to self-driving cars, from the Tax Authorities to a rotating door.

On Tuesday December 19, Museum Boerhaave, the Lorentz Center and eLaw organize a public lecture on ‘Fairness and Accountability of Sociotechnical Algorithmic Systems’.

As partner within the EuDEco-poject, the Centre for Law and Digital Technologies (eLaw) organized a panel titled “Filling accountability holes in algorithmic networks” as part of the 11th annual conference on Computers, Privacy and Data Protection (CPDP), January 24-26 2018 in Brussels.