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

In november 2023 is Anne Fleur van Veenstra, wetenschappelijk directeur van TNO Vector, benoemd tot bijzonder hoogleraar ‘Governance van data en algoritmen voor stedelijk beleid’.

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…

When can a patient be discharged from intensive care? Artificial intelligence can help answer this and other questions. But using such revolutionary technology in healthcare is not easy, as Anne de Hond has discovered.

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…

The lecture series

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 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…

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 lecture series “Humanity in the Automated State” concluded on 26 May 2026 at Leiden Law School with its closing lecture by Professor Natali Helberger from the University of Amsterdam.

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.

The lecture series 'Humanity in the Automated State' examines how AI and automated systems are transforming government and public administration and what it means to be human within these digitised institutions.

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…

Promotor: Prof.dr. P. Stevenhagen, Co-promotor: Prof. dr. B. de Smit

Interactive exploration of large volumes of data is increasingly common, as data scientists attempt to extract interesting information from large opaque data sets. This scenario presents a difficult challenge for traditional database systems, as (1) nothing is known about the query workload in advance,…

This thesis describes the Multi-site All-Sky CAmeRA (MASCARA), which consists of two small robotic telescope designed to detect exoplanets around the brightest stars in the sky.

What if you could watch a CT scan live, instead of analysing the images afterwards? If it is up to the Leiden mathematician Jan-Willem Buurlage, that will soon be a reality. He is developing methods to make the algorithms behind 3D scans faster. Quite a challenge: ‘Just like mathematicians, computers…

Promotores: Bas Edixhoven, Jean-Benoit Bost, Co-promotor: Robin de Jong

Promotor: Prof. dr. I. Snellen, Co-Promotor: Dr. M. Kenworthy

Natural Computing investigates algorithms and phenonema based on nature to create better and new computer science innovations.

By comparing individual health data with population data, doctors can provide personalized health advice and patients can learn from each other's experiences. Wessel Kraaij, professor of Applied Data Analytics shows how personal data can have predictive value.

The ability to collect and interpret huge quantities of data has become indispensable to society and academia. Leiden University is a knowledge and expertise centre for data science that places the emphasis on interdisciplinary collaboration and innovation.

In this project we develop algorithms to automatically detect a particular type of archaeological sites in satellite images of the Alps.

Less than 1 in 10 drug candidates that enter phase 1 clinical trials actually gets approved for human use.

NimbleAI aims at solutions for ultra-energy efficient and secure neuromorphic sensing and processing at the edge.

On 12 September 2019, Michiel Rhoen defended his thesis 'Big Data, Big Risks, Big Power Shifts: Evaluating the General Data Protection Regulation as an instrument of risk control and power redistribution in the context of big data'. The doctoral research was supervised by Prof. G.J. Zwenne and Prof.…

Quantum Delta NL, a research programme in which Leiden University participates, has been awarded 615 million euros from the National Growth Fund to help develop the Netherlands into a top player in quantum technology.