The quest for Trustworthy AI is high on both the political and the research agenda, and it actually constitutes TAILOR’s first research objective (H1) of developing the foundations for Trustworthy AI. It is concerned with designing and developing AI systems that incorporate the safeguards that make…

Data science is now growing fast in many places, but scholars at Leiden University have been developing data science techniques for a long time already. Thanks to their broad-based expertise, Leiden statisticians are currently combining the achievements in statistics with the latest methods of statistical…

The AiChemist project (https://aichemist.eu) coordinated by Helmholtz Munich is an Innovative Doctoral Training Network funded through the Marie Skłodowska-Curie Actions (MSCA-DN) within the EU Horizon Research Framework, to the sum of €3 million. It brings together leading experts in AI, chemoinformatics…

DSE 2.0 concerns research on DSE techniques for complex dCPS

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.

Music and language both communicate through sound, including timing and pitch. While language mainly conveys semantic meaning, instrumental music does not, and is typically seen as expressing emotion. This project investigates how well listeners recognize intended expressive feelings in music, instructed…

This is an Erasmus+ International Credit Mobility project of Leiden University’s Faculty of Science with University of California.

In this thesis we explore machine and deep learning approaches that address keychallenges in high dimensional problem areas and also in improving accuracy in wellknown problems. In high dimensional contexts, we have focused on computational fluid dynamics (CFD) simulations.

Promotor: Prof.dr. T.H.W. Bäck

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

Addressing the core novel objective of scalably assessing the impact of possible interventions through counterfactual prediction based on spatio-temporal data.

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

Hass

The Ada Lovelace Distinguished Lecture Series brings outstanding computer scientists from around the world to Leiden University. The lecturers will share exciting ideas and results from the forefront of computer science.

In design optimization problems, engineers typically handcraft design representations based on personal expertise, which leaves a fingerprint of the user experience in the optimization data. Thus, learning this notion of experience as transferrable design features has potential to improve the performance…

Read all papers and other types of publication created by the project.

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.

The master's specialisation Data Science: Computer Science at Leiden University provides students thorough knowledge and understanding of statistical and computational aspects of data analysis, including their application in databases, advances in data mining, networks, pattern recognition, and deep…

Real-life processes are characterized by dynamics involving time. Examples are walking, sleeping, disease progress in medical treatment, and events in a workflow.

This master’s programme combines Physics with Data Science. You will learn how physics has its own tricks to deal with big data and how techniques from machine learning and deep learning can be applied to classical and quantum data. The first focus of attention is on classical data, including data mining,…

At Leiden University, researchers from all disciplines work together to find answers and design innovations in the field of artificial intelligence.

The Faculty of Science

Quantum computing represents a fundamentally new computational paradigm, capable of addressing problems that are intractable for classical computers.

Collecting data in sports increased in importance the last few years.

Quantum computing is a novel paradigm for computation, which is nearing real-world impact with the coming generation of limited, but nonetheless powerful quantum devices.

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.

Micro-credentials make education for professionals even more accessible. If you follow a module of 3 to 30 EC (European Credits), you receive a micro credential after completing the education program. This digital certificate is recognized by 22 universities of applied sciences and 12 universities.

Course

Developing new medicines is one of modern science's most significant hurdles, a process marked by high costs, long timelines, and frequent failures of promising candidates.

Cancer is the leading cause of death in the Netherlands, and, with over 100 different types of cancer, it’s not a simple disease. Today, skin, breast, lung, prostate and colon cancer are the most diagnosed forms. Therefore, the discovery and development of new drugs has the ability to significantly…

The archaeological heritage of South America is facing increasing threats due to the expansion of agricultural activities, infrastructure expansion, illegal wood harvesting, and the current fire emergency plaguing the Amazon and other biomes of the continent.

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.

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.