Promotor: C. W. J. Beenakker, Co-promotor: J. K. Asboth

Industrial manufacturing processes, such as the production of steel or the stamping of car body parts, are complex semi-batch processes with many process steps, machine parameters and quality indicators.

The Data-Driven Drug Discovery Network (D4N) is an initiative by researchers from Leiden University and collaborators to join efforts in applying and developing novel techniques from data science to drug discovery and related topics from bioinformatics.

The use of increasingly large and diverse datasets to guide urban climate action has implications for how, and by whom, local governments are held accountable.

Predictive maintenance (PdM) is a maintenance policy that uses the past, current, and prognosticated health condition of an asset to predict when timely maintenance should occur.

The key characteristic of active matter is the motion of an emergent collection (such as a flock of birds), which is driven by the consumption of energy by its active components (i.e. individual birds).

On 7 February 2019, Helena Ursic-Vrabec defended her thesis 'Uncontrollable: Data subject rights and the data- driven economy'. The doctoral research was supervised by Prof. dr. S. van der Hof.

The role of material production as a driver of environmental impacts is increasing, which calls for a better understanding of global material flows. This thesis explores the role of in-use stocks of products, buildings and infrastructure as a key driver of global material demand and discusses the implications…

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.

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

Machine Learning is becoming a more and more substantial technology for industry.

Promotores: Prof.dr. T.H.W. Bäck, Prof.dr. M.R.V. Chaudron, Co-Promotor: M.T.M. Emmerich

Indigenous Latin American artifacts have attracted the interest of Europeans since the earliest moment of contact between Europeans and the Indigenous peoples of the Americas. The ERC-funded BECACO project uses an innovative multidisciplinary framework to investigate the provenance of ethnographic and…

Promotor: Prof.dr. B.R. Katzy, Co-promotor: R. Ortt

The research in this dissertation aims to optimise blood donation processes in the framework of the Dutch national blood bank Sanquin. The primary health risk for blood donors is iron deficiency, which is evaluated based on donors' hemoglobin and ferritin levels.

Nature uses a special class of histone proteins, histone variants, to modulate the properties of chromatin at defined genomic locations.

This thesis investigates the application of deep learning techniques in image analysis across various domains, focusing on four main themes: feature extraction, classification, segmentation, and integration, demonstrating the transformative potential of these technologies.

Promotor: Prof.dr. T. Hankemeier, Co-promotor: R.J. Vreeken

This thesis focuses on the development of sample-preparation methods for small amounts of samples and applying the developed methods to muscle tissues to investigate the mechanisms involved in sarcopenia.

This article provides an in‐depth assessment of lone actor terrorists’ attack planning and preparation.

This thesis seeks to investigate how cancer-associated mutations affect the pharmacological properties of selected GPCRs—primarily A2AAR and 5-HT2CR—through a combination of ligand binding assays, signaling readouts, kinetic profiling, and cellular functional assays.

More collaboration, combining data and asking the right questions. These are a few of the recommendations that policymakers and researchers formulated at the conference 'Data gedreven Beleidsontwikkeling' on 28 November 2017.

Dr. Sarah Giest presented her paper on Digital Access, Data-Driven Policymaking and Public Service Delivery during a research feedback seminar.

The housing crisis is affecting a substantial group of Dutch citizens and is one of the main election themes this year. How did things get this far and what should the new cabinet do in the coming four years to address the problems? Three Leiden researchers give their answer.

The studies presented in the work show the potential of the integrative use of biophysical data in defining the structural basis of protein interactions.

Creation of a framework for environmental parameter estimation that benefits from the consistency of physics-based theory-driven models and the accuracy of the machine-learning-based data-driven models

To argue that people can control the relative contributions of goal-driven and stimulus-driven processes to decision-making and action selection.

As a virtually inexhaustible source, solar energy plays a major role in future global energy scenarios.

This book explains how mass killing is driven by elite politics within authoritarian regimes.

Leiden University Centre for Linguistics (LUCL) is a reputable institute in the field of linguistics, offering excellent research and education opportunities covering a broad range of languages of the world.

Welcome to Leiden University Green Office!

The overarching aim of this theme is to increase our understanding of the mechanisms underlying altered cognitive, affective, and social behavior in relation to mental health problems.

A major goal of ABS research is to overcome one of the major bottle-necks in metabolomic research: the lack of a high-throughput infrastructure in which thousands of samples can be processed in a standardized and cost-effective way (max. a few tens of Euro’s per sample for a full metabolome profile).…

Promotor: J.G.E.M. Fraaije, Co-Promotor: A. Kros

The project ‘Food citizens? Collective food procurement in European cities: solidarity and diversity, skills and scale’ has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 724151).

The core of Leiden University's vision is to train students to become academic professionals and engaged, responsible citizens. Once they have graduated, out students will then be able to make a contribution to resolving the challenges currently facing society - both within and outside academia.

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

You can do a degree in Artificial Intelligence at Leiden University, but its role is also increasing in other degree programmes.

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In this research project, we aimed to obtain more insight in the role of mast cells in the immune driven disorders rheumatoid arthritis and atherosclerosis.

From development of nanomaterials to advanced instrumentation and smart software systems, this specialisation empowers students to become a key player in tomorrow’s technological breakthroughs—through interdisciplinary research, industrial collaboration, and innovation-driven learning.

The formation of stars and planets happens over multiple scales, which can interact. In particular, planet formation happens in the dense, complex environment of star forming regions.

Leiden is a lively university city, brimming with history and boasting a student life that’s tangible just about everywhere.

The minor Artificial Intelligence, Business & Innovation will provide you with knowledge and skills on the intersection of the fields of artificial intelligence, management, and entrepreneurship, with a focus on programming, technology management, entrepreneurial innovation, and ethical considerations…

What are the values that Leiden University cherishes? What does the University stand for and what does it consider important?

On the university's birthday (8 February), pupils in the final year of junior schools in Leiden and The Hague will have lessons from a real professor.

The Faculty of Law

The research programme Statistical Science is concerned with the analysis and interpretation of masses of data, the quantification of uncertainty using probability models, and the development and benchmarking of algorithms and methods with these aims.