This project will transform OpenML, a platform for sharing and creating datasets and AI models transparently and collaboratively, into a next-generation open science infrastructure.

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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.

How can the LEGO® Serious Play® method contribute to improved interdisciplinary collaboration and the development of joint research proposals?

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…

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

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

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…

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.

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

Making systems biology modelling a central pillar of research in biology

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

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.

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?

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.

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…

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.

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.

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

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.

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

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.

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.

Promotor: Prof.dr. J.N. Kok

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

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

Lecture

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

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.

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

In this thesis, topics relating to the optimization of high-throughput pipelines used for imaging are discussed. In particular, different levels of implementation, i.e., conceptual, software, and hardware, are discussed and the thesis outlines how advances on each level need to be made to make gains…

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

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

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

OpenML empowers scientists to conduct transparent, reproducible, and collaborative AI-driven research.

Exploring the integration of AI and quantum computing, this study adapts Knowledge Representation and Reasoning (KRR) to enhance quantum circuit simulation and optimization.

The Leiden Institute of Advance Computer Science (LIACS) in collaboration with the Institute of Security and Global Affairs (ISGA) have developed the minor Cyber Security to provide students with a mixture of technical and governance knowledge to set them on a path towards understanding cyberspace and…

Exploring the application of game-theoretic frameworks to quantum physics, this study creates novel AI training methods for the precise control of quantum systems.

Exploring the application of data-driven AI optimizations, this work leverages past software performance to reduce the carbon footprint and energy consumption of powerful computing applications.

This project aims to develop a portable, real-time intelligent system tailored for speech disorder therapy.