589 search results for “machine” in the Public website
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Philipp Kropf
Science
p.kropf@cml.leidenuniv.nl | +31 71 527 2727
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Exploring big data approaches in the context of early stage clinical
Als gevolg van de grote technologische vooruitgang in de gezondheidszorg worden in toenemende mate gegevens verzameld tijdens de uitvoering van klinische onderzoeken.
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Network analysis methods for smart inspection in the transport domain
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.
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Algorithm selection and configuration for Noisy Intermediate Scale Quantum methods for industrial applications
Quantum hardware comes with a different computing paradigm and new ways to tackle applications. Much effort has to be put into understanding how to leverage this technology to give real-world advantages in areas of interest for industries such as combinatorial optimization or machine learning.
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Numerical exploration of statistical physics
In this thesis, we examine various systems through the lens of several numerical methods.
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Data-Driven Risk Assessment in Infrastructure Networks
Leiden University and the Ministry of Infrastructure and Water Management are involved in a collaboration in the form of a research project titled 'Data-Driven Risk Assessment in Infrastructure Networks'.
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A document classifier for medicinal chemistry publications trained on the ChEMBL corpus
Source: J Cheminform, Volume 6, Issue 1 (2014)
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Data-driven Predictive Maintenance and Time-Series Applications
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.
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Model-assisted robust optimization for continuous black-box problems
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.
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Methods and Tools for Mining Multivariate Time Series
Mining time series is a machine learning subfield that focuses on a particular data structure, where variables are measured over (short or long) periods of time.
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Robust rules for prediction and description.
In this work, we attempt to answer the question:
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Spectral imaging and tomographic reconstruction methods for industrial applications
Radiography is an important technique to inspect objects, with applications in airports and hospitals. X-ray imaging is also essential in industry, for instance in food safety checks for the presence of foreign objects.
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Structured Parallel Programming for Monte Carlo Tree Search
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.
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Tom Kouwenhoven
Science
t.kouwenhoven@liacs.leidenuniv.nl | +31 71 527 4799
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Julia Wasala
Science
j.wasala@liacs.leidenuniv.nl | +31 71 527 4799
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Surendra Balraadjsing
Science
s.balraadjsing@cml.leidenuniv.nl | +31 71 527 2727
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Chen Li
Science
c.li@cml.leidenuniv.nl | +31 71 527 2727
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Using cryo-EM methods to uncover structure and function of bacteriophages
Bacteriophages, or phages for short, are the most abundant biological entity in nature. They shape bacterial communities and are a major driving force in bacterial evolution.
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Data science for tax administration
In this PhD-thesis several new and existing data science application are described that are particularly focused on applications for tax administrations.
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Nurbolat Kenbayev
Science
n.kenbayev@liacs.leidenuniv.nl | +31 71 527 2727
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Gerard van Westen
Science
gerard@lacdr.leidenuniv.nl | +31 71 527 3511
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Rayyan Toutounji
Faculteit der Sociale Wetenschappen
r.toutounji@fsw.leidenuniv.nl | +31 71 527 2727
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Guilherme D'Andrea Curra
Faculteit Archeologie
g.dandrea.curra@arch.leidenuniv.nl | +31 71 527 2727
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Diego Barbosa Arize Santos
Faculteit der Sociale Wetenschappen
d.barbosa.arize.santos@fsw.leidenuniv.nl | +31 71 527 2727
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Data Driven Modeling & Optimization of Industrial Processes
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.
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Calculated Moves: Generating Air Combat Behaviour
By training with virtual opponents known as computer generated forces (CGFs), trainee fighter pilots can build the experience necessary for air combat operations, at a fraction of the cost of training with real aircraft.
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Automated de novo metabolite identification with mass spectrometry and cheminformatics
Promotor: Prof.dr. T. Hankemeier, Co-Promotores: T. Reijmers, L. Coulier
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Filter-based reconstruction methods for tomography
Promotor: K.J. Batenburg
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POST_SIGNATURE
To what extent is creative ownership in contemporary (graphic) design practices changing now that we are co-creating with machines? And can machines have copyrights, too?
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Our facilities
In support of the research and education, the Leiden Institute of Advanced Computer Science (LIACS) has a Research and Education laboratory at its disposal. Within this environment, we can offer machines that go beyond normal office automisation and production.
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Applied Machine Learning in Neurosurgical Oncology
PhD defence
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Novel analytical approaches to characterize particles in biopharmaceuticals
Particles are omnipresent in biopharmaceutical products. In protein-based therapeutics such particles are generally associated with impurities, either derived from the drug product itself (e.g. protein aggregates), or from extrinsic contaminations (e.g. cellulose fibers).
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Socially Embedded AI Systems
This interdisciplinary research project explores several adaptive machine learning methods which can give insight into the interaction between human and machine. The ultimate goal is open and natural communication between humans and AI that should result in mutual trust, cooperation and coordination…
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Webinars
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.
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High-contrast spectroscopy of exoplanet atmospheres
More than 5,000 exoplanets have been found over the past couple of decades. These exoplanets show a tremendous diversity, ranging from scorching hot Jupiters, common super-Earths, to widely separated super-Jupiters on the planet/brown dwarf boundary.
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Learning from small samples
Learning from small data sets in machine learning is a crucial challenge, especially when dealing with data imbalances and anomaly detection. This thesis delves into the challenges and methodologies of learning from small datasets in machine learning, with a particular focus on addressing data imbalances…
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Pascal chair 2023
Peter Flach is Professor of Artificial Intelligence at the University of Bristol. An internationally leading scholar in the evaluation and improvement of machine learning models using ROC analysis and calibration, he has also published on mining highly structured data, on knowledge-driven and explainable…
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Discovering the preference hypervolume: an interactive model for real world computational co-creativity
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.
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Flagships
In CCLS several subgroups have formed, below you can find an overview of these groups with the names of the leading researchers and a short outline of the project.
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Artifical intelligence gets a boost from quantum computing
Machine learning - on classical computers- has made great progress in the past five years. Computer translation of speech and text is just one example. In Leiden, some researchers expect that machine learning, empowered by quantum systems, even if they only contain a few dozen qubits, can lead to a…
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Previous SAILS Workshops
SAILS likes to occasionally organise workshops about topics that relate to our programme. On this page you can find more information about previous workshops.
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BNAIC/Benelearn conference big success
Reinforcement learning, agents and classification: these are just some of the topics researchers on Artificial Intelligence and Machine Learning discussed at the BNAIC/BeneLearn conference 2020. It was the first time Leiden University hosted the annually held Belgium Netherlands Artificial Intelligence…
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Alex Brandsen
Faculteit Archeologie
a.brandsen@arch.leidenuniv.nl | +31 71 527 2727
- Publications
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Automated Design and Analysis of Algorithms
The Automated Design and Analysis of Algorithms (ADA) research group pursues the development of Artificial Intelligence techniques that complement, rather than replace, human intelligence.
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Reduction of single use coffee cups
The goal is to reduce single use coffee cup use both at the university cafés and cofee machines.
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Translation
Empirical and experimental research focusing on literary, legal, medical and audiovisual translation.
- Data Science & Artificial Intelligence
- Meet our staff
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Proteins in harmony: Tuning selectivity in early drug discovery
This thesis describes the importance of being able to control the selectivity of potential drug candidates.