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

Promotor: Prof.dr. T.H.W. Bäck

Time-series forecasting through modelling sequences of temporally dependent observations has many industrial and scientific applications. While machine learning models have been widely used to create time-series forecasting models, creating efficient and performant time-series forecasting models is…

In this thesis we study bistable reaction-diffusion equations on lattice domains.

Promotor: J.N. Kok, Co-Promotor: A.J. Knobbe

Promotor: M.T.M. Koper, Co-promotor: J.B.F. Juurlink

Promotor: R. Gill, Co-promotor: P. Massart

It is a common technique in global optimization with expensive black-box functions to learn a surrogate-model of the response function from past evaluations and use it to decide on the location of future evaluations.

This dissertation presents the synthesis and evaluation of antibody recognition for various capsular polysaccharide (CP) fragments of Staphylococcus aureus (S. aureus).

The global agri-food system plays a critical role in food security and environmental issues.

Promotores: Prof.dr. G.A. Persoon & Prof. dr. H.H. de Iongh

Op 7 februari 2019 verdedigde Helena Ursic-Vrabec haar proefschrift 'Uncontrollable: Data subject rights and the data- driven economy'. Het promotieonderzoek is begeleid door promotor prof. dr. S. van der Hof.

Promotores: Prof.dr. H.J.M. de Groot, Prof.dr. J. Matysik (Universitaet Leipzig)

Promotor: Prof.dr. E. Bouwman, Co-promotor: S. Bonnet

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

The majority (80%) of e-waste generated globally are recycled informally in developing countries.

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

This dissertation explores how we can make anomaly detection—identifying unusual or faulty behavior in complex systems—more trustworthy and effective, with a focus on smart manufacturing.

Synthetic hydrogels that mimic the natural extracellular matrix in the biophysical and biochemical cues it provides to cells are in high demand, however the cell phenotypes as they are observed in vivo in numerous cases have yet to be attained.

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

To this day, all cyclophellitol-based inhibitors and ABPs have been close analogues of their natural substrate counterparts. As a result, these probes showed high selectivity towards their target glycosidases.

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…

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…

Multi-objective evolutionary computation aims to find high quality (Pareto optimal) solutions that represent the trade-off between multiple objectives.

Cryogenic electron microscopy (cryo-EM) is a powerful technique used to visualize the inside of cells and to study specific protein complexes. Within this thesis, I describe the use of various cryo-EM techniques to gain insight into the structural changes of the human pathogen, Vibrio cholerae, as it…

Promotores: Prof.dr. T.H.W. Bäck, Prof.dr. M. Bongards (Cologne University)

Actinobacteria are Gram-positive bacteria that have a complex multicellular life cycle and are well known for their ability to produce a wide range of bioactive natural products (NPs).

Computers zijn in staat om ongelooflijk nauwkeurige voorspellingen te doen op basis van machine learning. Met andere woorden, deze computers kunnen zonder tussenkomst leren als ze eenmaal door mensen zijn voorgeprogrammeerd. Bij LIACS verkennen en verleggen we de grenzen van wat een revolutionaire nieuwe…

Human AI is waar kunstmatige intelligentie en machine learning samenkomen met filosofie, cognitieve wetenschap en de creatieve kunsten. Voorbeelden van onderzoeksvragen in dit domein zijn: ‘Kan een algoritme naar menselijke maatstaven creatief zijn?', 'Kunnen creatieve processen, zoals het componeren…

Je kunt aan de Universiteit Leiden Kunstmatige Intelligentie studeren, maar ook binnen andere opleidingen speelt het een steeds grotere rol.

Learning a programming language is challenging. Even one of the first –but crucial– concepts to learn, variables, is hard to grasp. Variables can represent different roles and functions within a code and need to be named appropriately to support code comprehension and debugging.

The aims of the project are to: further clarify 'inhibition by safety'; explore and describe all possible sagety factors, with a special focus on the primary human safety source: social connectedness; reviewing prolonged stress responses without stressors.

How do you engage society to stop biodiversity loss? How do you create political and social involvement to deal with climate change? And how do you balance the economic needs of industry with the negative effects of pollution? If you find these kinds of questions interesting, then this Pre-University…

Het project XAIPre (spreek uit als

Studievoorlichting

This thesis describes the synthesis, analysis of various tetrazine bearing compounds and use in bioorthogonal chemistry.

De onderzoeksgroep Business, Technology & Public Policy van de afdeling Bedrijfswetenschappen van Universiteit leiden houdt zich bezig met het onderzoeken van de dynamische wisselwerking tussen ‘nieuwe’ technologieën en de verschillende belanghebbenden die hiermee interacteren, waaronder consumenten,…

Op 15 juli 2019 heeft Hans-Martien ten Napel de aftrap gegeven voor een nieuwe serie over het recht op vrijheid van godsdienst en levensovertuiging op het interdisciplinaire Religion and Global Society Blog van de London School of Economics.

Het verzamelen en interpreteren van grote hoeveelheden data is niet meer weg te denken uit de maatschappij en de wetenschap. De Universiteit Leiden is een kennis- en expertisecentrum van data science dat de nadruk legt op interdisciplinaire samenwerking en innovatie.