Existing work in probabilistic language modeling can be mostly divided into two categories:

With the emergence of online social networks (OSNs), the way people create and share information has changed, which becomes faster and broader than traditional social media.

This thesis deals with the use of sound in interactions in the context of participatory systems and data sonification. We investigate an interactive environment where participants perceive information of the data through sound elements.

The Leiden Institute of Advanced Computer Science (LIACS) aims on doing applied research with partners. You can be involved in our research, and in the knowledge transfer of our research results.

This thesis probes under what conditions quantum computing presents an advantage over classical computing.

SAILS is a university wide initiative aimed at facilitating collaboration across disciplines on the use of Artificial Intelligence (AI).

Lecture

This interdisciplinary project applies data science techniques to qualitatively and quantitatively visualize the interaction between the University and the city of Leiden (Town&Gown) from 1575 onwards. One of the possible angles for follow-up research is diversity, especially from the international…

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.

Lecture

Researchers using remote sensing technologies have characterized pre-Columbian regularly-shaped earthworks in forests in Central America and the Amazon. In tropical forested mountains in South America, two challenges arise when identifying archaeological sites through remote sensing. Firstly, sites…

FAIRDOM consortium is an open initiative of various partners including funding programmes, large-consortia, institutes, small groups as well as individuals.

Promotor: Prof.dr. H.A.G. Wijshoff

In this work we describe three methods to improve the performance of Quantum Field Theory calculations.

The database research community has made tremendous strides in developing powerful database engines that allow for efficient analytical query processing.

Today, knowledge is the most crucial element to stimulate organizational competitiveness and economic development.

Promotor: Prof.dr. J.N. Kok, Co-promotor: F.J. Verbeek

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

Humans share meaning through language. Over time, repeated interactions have shaped languages into forms that match our cognitive preferences, making them structured, expressive, easy to learn, and ultimately, meaningful.

Today, everybody and everything produces data. People produce large amounts of data in social networks and in commercial transactions. Medical, corporate, and government databases continue to grow. Sensors continue to get cheaper and are increasingly connected, creating an Internet of Things, and generating…

In this thesis, we have studied cell images from two types of cells, including pollen grains and the immune cells, neutrophils. These images are captured using a bright field microscope and a confocal microscope.

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.

Study information

Both on a personal and institutional level, the staff of Leiden CADS collaborates with:

This inaugural lecture discusses the question: How to cooperate in the digital era?

Promotor: Prof.dr. J.N. Kok

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

Quantum computers are a proposed fundamentally new type of computer. They aim to perform some computations much faster than previously possible by exploiting phenomena at the quantum scale, called superposition and entanglement.

This project aims to develop advanced data analysis methods for monitoring and increasing our understanding on biodiversity dynamics in nature reserves such as the Oostvaardersplassen.

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…

In this PhD project, we focus on improving the effectiveness and efficiency of LMs with narrative data.

This thesis advances automata learning, a key area in computer science, with applications in software verification, biological analysis, and autonomous technologies. It explores three main themes: first, it introduces a passive learning algorithm for generating compact probabilistic models from positive…

Image-Pro Plus, ImageJ, Cell Profiler, R, Knime and NIS-elements

A convolutional neural network (CNN) is a biologically inspired algorithm, highly capable at processing images and videos.

Uncertainty and noise are frequently-encountered obstacles in real-world applications of numerical optimization. The practice of optimization that deals with uncertainties and noise is commonly referred to as robust optimization.

Making systems biology modelling a central pillar of research in biology

We are living in an information era where the amount of image and video data increases exponentially.

A new initiative has started at Leiden University and at Leiden Institute for Advanced Computer Science (LIACS) in particular. Where SAILS is more geared towards Leiden University and the LUMC itself, the newly developed AI Collaboration Centre aims to forged alliances with the (local) government, companies…

Promotor: J.N. Kok, Co-promotor: H.J. Hoogeboom

This thesis mainly focuses on cross-modal retrieval and single-modal image retrieval via deep learning methods, i.e. by using deep convolutional neural networks.

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.

Patients share valuable advice and experiences with their peers in online patient discussion groups.

The newly developed AI Collaboration Centre aims to forged alliances with the (local) government, companies and other educational institutes.

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.

The focus of this thesis is on the technical methods which help promote the movement towards Trustworthy AI, specifically within the Inspectorate of the Netherlands.

Transport inspectorates are looking for novel methods to identify dangerous behavior, ultimately to reduce risks associated to the movements of people and goods. We explore a data-driven approach to arrive at smart inspections of vehicles.

Software development is a complex process. It is important that software products become stable and maintainable assets.

Connect theory and practice of teaching through the application of your academic knowledge about computer science to issues of classroom practice.