A neural network mimics how our brain works. Evolutionary algorithms use the principle of natural selection to solve complex problems. This kind of 'natural computing' is being used to improve the diagnosis of Parkinson's disease or the production of steel.

Lecture

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.

The correctness of computational systems is of great importance to our society, since it becomes ever more reliant on the benefits of computing.

Promotor: H.W. Lenstra

We show that Kirchhoff ’s law of conservation holds for non-commutative graph flows if and only if the graph is planar. We generalize the theory of (Euclidean) lattices to infinite dimension and consider the ring of algebraic integers as such a lattice.

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.

Promotor: S.J. Edixhoven, L.D.J. Taelman

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: K.H. Kuijken

Promotor: J.P. Abrahams, Co-Promotor: N.S. Pannu

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

Lecture

PhD defence

Tic tac toe, but with quantum effects. That makes learning the principles of quantum technology a piece of cake. This is the aim of a new start-up founded by researcher Evert van Nieuwenburg: QuantumPlayed. ‘Quantum is all around us and everyone should be able to learn about it.’

PhD defence

PhD defence

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 majority of scientists, from archaeologists through to zoologists, collect enormous volumes of data. Their massive databases contain large amounts of information which is difficult for humans to filter. With a solid grounding in statistics and computer science, we can develop algorithms for analyzing…

Leiden Institute of Advanced Computer Science (LIACS)

The project XAIPre (pronounce “Xyper”) aims to develop predictive maintenance system for the maritime industry using sensor technology and artificial intelligence. The project aims at developing Explainable Predictive Maintenance (XPdM) algorithms that do not only provide the engineers with a prediction…

NeuroSoC concentrates on multiprocessor systems on chip with in-memory neural processing units.

An integrated approach for the simultaneous prediction of polypharmacology and binding affinity/potency of small molecules.

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.

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…

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

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

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: C.W.J. Beenakker, Co-Promotor: A.R. Akhmerov

Promotores: T.H.W. Bäck, A. Plaat, Co-promotor: F.J. Verbeek

This dissertation derives from the development of tools for algorithmic composition which extract pitch materials from sound signals, analyzing them according to their timbral and harmonic properties, putting them into motion through diverse rhythmic and textural procedures.

Gibbs processes, g-measures, fuzzy Gibbs states

A common method to solve expensive function evaluation problem is using Bayesian Global Optimization, instead of Evolutionary Algorithms.

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.

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.

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.

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’.

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.

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

The Leiden Computational Network Science Lab (CNS Lab) researches methods for knowledge discovery from real-world network data.

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

The Reinforcement Learning lab conducts research into Reinforcement Learning and Intelligent Combinatorial Algorithms.

Seminar

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.

AI MAPS adopts a freedom and social well-being perspective and focuses on three themes to address key security challenges; Social disorder and public nuisances in neighbourhoods, High-impact crime, and Crowds and events.

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

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,…