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…

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

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.

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.

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

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

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

Het onderzoek dat wordt gedaan binnen het Instituut Politieke Wetenschap heeft als gemene deler dat er vanuit verschillende politicologische sub-disciplines wordt gekeken naar de dynamiek van en wisselwerking tussen politieke instituties, individuele besluitvorming en collectief gedrag.

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.

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

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…

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

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.

Promotor: Robert Tijdeman, Co-promotor: Cornelis Kraaikamp

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

We present an extensive study of methods for exactly solving stochastic constraint (optimisation) problems (SCPs) in network analysis. These problems are prevalent in science, governance and industry.

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.

Wat is het effect van maatschappelijke veranderingen, persoonlijke levensomstandigheden en migratiebeleid op iemands besluit te migreren?

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…

Multi-criteria optimalisatie is een effectieve techniek voor het vinden van optimale oplossingen die een afweging bieden tussen verschillende, tegenstrijdige criteria. Het heeft zijn toepassing gevonden in de wereld om ons heen omdat bij het oplossen van praktische, re¨ele wereld problemen men gewoonlijk…

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.

Welke politieke factoren beïnvloeden de snelheid of duur van de wetgevingsbesluitvorming in de EU?

Studies naar perceptuele besluitvorming presenteren dezelfde stimulus doorgaans herhaaldelijk tijdens een experimentele sessie, maar negeren de volgorde van deze observaties, waarbij wordt uitgegaan van een onrealistische stabiliteit van beslissingsstrategieën tijdens proeven. Maar zelfs ‘stabiel’,…

Deze scriptie onderzoekt de complexiteit van wetsbesluiten binnen de EU, met een specifieke focus op de Raad van de EU.

Elke dag nemen we vele beslissingen; van wat we eten tot hoe we de wereld om ons heen interpreteren. Over het algemeen gingen onderzoekers ervan uit dat een belangrijk onderdeel van ons besluitvormingsproces, namelijk het beslissingscriterium, stabiel blijft. Er zijn echter steeds meer aanwijzingen…

In this special edition of Information Polity there is a focus on the transparency challenges of using algorithms in government in decision-making procedures at the macro-, meso-, and micro-levels.

Team Syntax Error, met Bas Nieuwenhuizen, Mathijs van de Nes, Niels ten Dijke, alle drie masterstudenten Computer Science, heeft de Benelux Algorithm Programming Contest gewonnen en heeft zich daarmee geplaatst voor de Northwestern European Regional Contest in Zweden, op 29 en 30 november.

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.

Promotores: J.N. Kok, H.J. Hoogeboom

Computers worden steeds krachtiger en krijgen steeds ingewikkelder taken. Het Leiden Institute of Advanced Computer Science (LIACS) doet baanbrekend wetenschappelijk onderzoek en past nieuwe vindingen toe in actuele maatschappelijke vraagstukken.

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Het Leidse team 'Geen Syntax', bestaande uit Bas Nieuwenhuizen, Mathijs van de Nes en Raymond van Bommel, heeft in Utrecht de Benelux Algorithm Programming Contest (BAPC) 2013 gewonnen. Deze Leidse studenten wiskunde en informatica losten de 10 opgaven een uur sneller op dan alle andere teams.

De coronacrisis is de ultieme test voor bestuurders. Hoe houden nationale politieke leiders zich staande in hectische, dynamische tijden? Martin Lodge (London School of Economics and Political Science) en (Arjen Boin (Instituut Politieke Wetenschap Universiteit Leiden) bekijken de ervaringen opgedaan…

Despite being the object of intense study, embryonic development has been difficult to model due to a number of reasons. First, complex tissues can be comprised of many cell types, of which we probably only know a subset.

Op 20 maart 2019 verdedigde Tim Dekkers zijn proefschrift 'Mobility, Control and Technology in Border Areas: Discretion and Decision-making in the Information Age'. Het promotieonderzoek is begeleid door promotoren prof. dr. J.P. van der Leun en prof. dr. M.A.H. van der Woude.

Promotor: A.P.IJzerman Co-promotor: A. Bender

There is a need for alternative methods to replace, reduce and refine (3R) animal experimentation. Combining experimental data from high-throughput in vitro studies with in silico modeling is a promising approach to unravel the effect of chemicals on living cells and to gain a better understanding of…

In dit artikel wordt het concept van probleemprioritering binnen de context van bestuurskundig onderzoek verkend.

In dit artikel onderzoekt Amandine Lerusse hoe de volgorde van prestatie-informatie de prioriteringsbeslissingen van lokale politici beïnvloedt.

Promotie

The Behavioral Public Administration Lab (BPA Lab) conducts behavioral science to generate, share, and apply insights about human behavior to improve governance, policy, and management in the public sector.

This thesis involves three topics: benchmarking discrete optimization algorithms, empirical analyses of evolutionary computation, and automatic algorithm configuration.

Constraint multi-objective optimization with a limited budget for function evaluations is challenging. This thesis tackles this problem by proposing new optimization algorithms. These algorithms are applied on holistic ship design problems. This helps naval architects balance objectives like cost, efficiency,…

Promotor: H.W. Lenstra