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…

In this PhD-thesis several new and existing data science application are described that are particularly focused on applications for tax administrations.

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,…

We see computer programming as an essential skill. It enables you to be self-sufficient in building tools, processing data, visualizing research output, communicating research results, etc. Moreover, it empowers you to make beautiful things.

Leiden University computer scientists Yu Liu, Yanming Guo and Michael Lew are a step closer to their ultimate goal: search engines with visual recognition. Their publication of a new algorithm for fusing multi-scale deep learning representations has been received with great enthusiasm. No other algorithm…

Research in the Natural Computing and Optimization cluster covers theoretical foundations, the development of new algorithms, and interdisciplinary applications of natural computing methods.

Anne Meuwese and Francien Dechesne have received SSH Open Competition M funding from the Dutch Research Council for their joint project 'The Artificial Intelligence Act in action. Probing and improving the quality of legislation in the algorithmic era.'

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…

Computers are becoming ever more powerful and are taking on more complex tasks. The Leiden Institute of Advanced Computer Science (LIACS) contributes to revolutionary scientific research and applies the latest inventions in the field, offering answers to today’s questions of society.

Promotores: S.J. Edixhoven, P.Parent

The master’s specialisation Artificial Intelligence offers future-oriented topics in computer science with a focus on machine learning, optimization algorithms, and decision support techniques.

This thesis investigates the contribution of quantum computers to machine learning, a field called Quantum Machine Learning. Quantum Machine Learning promises innovative perspectives and methods for solving complex problems in machine learning, leveraging the unique capabilities of quantum computers…

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

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.

Lecture

We show that Kirchhoff ’s law of conservation holds for non-commutative graph flows if and only if the graph is planar. We generalize the theory of (Euclidean) lattices to infinite dimension and consider the ring of algebraic integers as such a lattice.

A neural network mimics how our brain works. Evolutionary algorithms use the principle of natural selection to solve complex problems. This kind of 'natural computing' is being used to improve the diagnosis of Parkinson's disease or the production of steel.

On this page you will find a collection of presentations and videos of the Florence Nightingale Colloquia, seminars at the faculty and other event recordings hosted by the Data Science Research Programme.

Promotor: S.J. Edixhoven, L.D.J. Taelman

Promotor: K.H. Kuijken

Promotor: S.J. Edixhoven

The Explainatory Data Analysis group develops algorithms and theory that enable domain experts to explain data by finding interpretable patterns and models.

Promotor: H.W. Lenstra

The correctness of computational systems is of great importance to our society, since it becomes ever more reliant on the benefits of computing.

This thesis mainly focuses on multimodal understanding and Visual Question Answering (VQA) via deep learning methods. For technical contributions, this thesis first focuses on improving multimodal fusion schemes via multi-stage vision-language interactions.

On 14 May 2020, Pieter Rustenburg defended his thesis 'Een algemene normtheorie toegepast op open normen in het belastingrecht'. The doctoral research was supervised by Prof. A.O. Lubbers and Prof. J.L.M. Gribnau.

Promotor: F. Arbab, R. De Nicola, Co-Promotor: M. Tribastone

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.

This dissertation advances automated negotiation by developing agents that can learn and adapt across diverse negotiation settings through three increasingly sophisticated approaches: automated algorithm configuration, portfolio-based strategy selection, and end-to-end reinforcement learning with graph…

The lecture series

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…

Which brain cell does what, when Parkinson's disease arises? It won't be long before this jigsaw is solved piece by piece. Ahmed Mahfouz, computational biologist, combines bio-knowledge from Leiden with algorithms from Delft and is getting closer to finding the key.

Research in this group, headed by Gerard van Westen, focusses on computational methods integrated in different parts of the drug discovery process. More specifically, topics include innovative treatments for cancer, selectivity modeling, translational research, allosteric modulation, drug resistance…

The majority of scientists, from archaeologists through to zoologists, collect huge volumes of data. Their massive databases contain large amounts of information which is difficult for humans to filter. With a solid grounding in statistics, we can develop algorithms for analysing and identifying patterns…

The Computers, Privacy and Data Protection Conference (CPDP) is the world’s leading multidisciplinary event on privacy and data protection. CPDP brings together experts to explore cutting-edge legal, regulatory, academic, and technological developments in the field, providing a premier platform for…

An integrated approach for the simultaneous prediction of polypharmacology and binding affinity/potency of small molecules.

The focus of the Bachelor Data Science & Artificial Intelligence is on computer science, and its applications in Artificial Intelligence. You will receive a strong basis in mathematics, statistics and computer science, combined with advanced knowledge of machine learning, cognitive science, human-robot…

The thesis is part of a bigger project, the HEPGAME (High Energy Physics Game). The main objective for HEPGAME is the utilization of AI solutions, particularly by using MCTS for simplification of HEP calculations.

NeuroSoC concentrates on multiprocessor systems on chip with in-memory neural processing units.

In this thesis it is posed that the central object of preference discovery is a co-creative process in which the Other can be represented by a machine. It explores efficient methods to enhance introverted intuition using extraverted intuition's communication lines.

Promotores: T.H.W. Bäck, A. Plaat, Co-promotor: F.J. Verbeek

Promotor: C.W.J. Beenakker, Co-Promotor: A.R. Akhmerov

This programme is aimed at students who have a strong interest in programming and computer science, as well as an interest in the cognitive psychology and artificial intelligence.

One of the key limitations of the direct imaging of exoplanets at small angular separations are quasi-static speckles that originate from evolving non-common path aberrations (NCPA) to which the primary adaptive optics system is inherently blind. The main focus of this thesis is the development and…

Through the microcredentials offered by the Faculty Science at Leiden University, you can take individual courses at university level.

This monograph focuses on clustering of objects in high-dimensional data, given the restriction that the objects do not cluster on all the attributes, not even on a single subset of attributes, but often on different subsets of attributes in the data.

With tomography it is possible to reconstruct the interior of an object without destroying.

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…