Urbanisation is steadily increasing with estimates expecting that 68% of the global population will live in cities by 2050. To accommodate the rural to urban transition, large quantities of land are transformed from natural to urban lands.

In deze opleiding streef je naar het beantwoorden van biologische vraagstukken in relatie tot milieu, ecologie en andere maatschappelijk relevante onderwerpen.

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

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…

Automated Machine Learning (AutoML) is widely used to automatically build a suitable practical Machine Learning (ML) model for an arbitrary real-world problem, reducing the effort of practitioners in the ML development cycle for real-world applications. Optimization is a key part of a typical AutoML…

Freshwater biodiversity has been threatened by eutrophication due to excessive nutrients in the environment. Releasing the freshwater species from such pressures requires efforts from industry and manufacturers to avoid emissions to vulnerable and high-risk regions.

All the data stored and processed by our computers is encoded as sequences of zeros and ones, called bits. Quantum computers offer an alternative to this traditional way of encoding and manipulating information.

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.

The focus of this thesis is on the technical methods which help promote the movement towards Trustworthy AI, specifically within the Inspectorate of the Netherlands.

Globally and regionally, biodiversity is declining and there are shifts in species’ occurrences and functional traits.

This thesis investigates the contribution of quantum computers to machine learning, a field called Quantum Machine Learning. Quantum Machine Learning promises innovative perspectives and methods for solving complex problems in machine learning, leveraging the unique capabilities of quantum computers…

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…

The marine shipping industry is one of the strongest emitters of nitrogen oxides (NOx), a pollutant detrimental to ecology and human health. Over the last 20 years, the pollution produced by power plants, the industry sector, and cars has been decreasing.

Sewer pipes are an essential infrastructure in modern society and their proper operation is important for public health. To keep sewer pipes operational as much as possible, periodical inspections for defects are performed.

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…

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The Vallesian, 11.1-9 Ma, was a special time in the Vallès-Penedes basin near Barcelona, where a biodiversity hotspot existed. Europe had a subtropical climate, with rhinos, forest giraffes, lions, hyenas, flying squirrels and primates.

The ongoing increase in antimicrobial resistance combined with the low discovery of novel antibiotics is a serious threat to our health care.

We explored how to morphologically classify well-resolved jetted radio-loud active galactic nuclei (RLAGN) in the LOw Frequency Array (LOFAR) Two-metre Sky Survey (LoTSS) using machine learning.

Freshwater and brackish water ecosystems are arguably the most vulnerable ecosystems on earth, due to concentrated human developments in and around them. The Pontocaspian (PC) region located at the border of Europe and Asia contains a variety of brackish water ecosystems and unique inhabitants, known…

Promotores: Prof.dr. J. Zaanen, Prof.dr. K.E. Schalm

Over onorthodoxe uitingen van wetenschap.

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

In this dissertation, we study partition-based models that can be used both for interpretable predictive modeling and for understanding data via interpretable patterns.

Eerlijke en creatieve AI

In this work, I explore the creation of new methods that optimize simulations of the gravitational N-body problem. Specifically, I take advantage of the recent popularity of Machine Learning methods to find tools that can suit this problem.

A management strategy has been developed for field margins to reduce pesticide drift to non-target areas and to promote biodiversity on arable land. To this end, 3 and 6 m wide strips along the edges of winter wheat, sugar beet and potato crops have been left unsprayed with herbicides and insecticides…

This thesis focuses on data found in the field of computational drug discovery. New insight can be obtained by applying machine learning in various ways and in a variety of domains. Two studies delved into the application of proteochemometrics (PCM), a machine learning technique that can be used to…

Promotors: Prof.dr. G.R. de Snoo, Prof.dr. G.A. Persoon, Prof.dr.ir. H.H. de Iongh

Seagrass is a marine flowering plant with special adaptations to coastal and marine environments, playing a crucial role in providing a wide range of ecosystem services.

This thesis focuses on enhancing predictions of central nervous system drug exposure using the LeiCNS-PK3.0, a physiologically based pharmacokinetic model.

In his dissertation Michiel Hooykaas outlines the results of six empirical research projects focused at biodiversity awareness in the Netherlands, specifically people’s knowledge about animals.

Cláudio de Sá voorspelt voorkeuren van mensen door gebruik te maken van ranglijsten. Dit doet hij door ‘klassieke’ machine learning-technieken aan te passen. Zijn werk kan onder andere gebruikt worden om de uitslagen van verkiezingen te voorspellen. Promotie op 16 december.

Onderzoekers uit de informatica, wiskunde, meteorologie, materiaalbouw natuur- en sterrenkunde hebben gezamenlijk een oplossing gevonden voor hun grote behoefte aan rekenvermogen. De diverse groep onderzoekers heeft voor de bouw van een revolutionaire supercomputer, die

Promotor: J.A. van Veen, Co-promotor: E.E. Kuramae

Ontwikkelingen om de mariene biodiversiteit met hoge resolutie te meten, door ernaar te luisteren.

This thesis addresses questions on effectively using variational quantum circuits for machine learning tasks.

Humans can see the world through the eyes of other humans and imagine what they know, want, and intend. This competence is known as Theory of Mind.

In this project, researchers from computer science, law, psychology, and public administration research in practice how artificial intelligence (AI) can be leveraged to make decision-making in the security domain more effective, while also keeping it safe and accountable.

This thesis probes under what conditions quantum computing presents an advantage over classical computing.

The application of nanomaterials in industrial processes and consumer products provides many societal benefits, but can also lead to the release of nanomaterials into the environment. The work in this dissertation aims to provide insights into the potential environmental impacts that may follow from…

‘We hopen dat ons artikel de mogelijkheden en voordelen laat zien van het gebruik van kunstmatige intelligentie in de quantumfysica om nieuwe ontdekkingen te doen.’ Vedran Dunjko van het Leiden Institute of Advanced Computer Science droeg bij aan een artikel dat vorig jaar verscheen in PNAS. Het artikel…

Plant diversity is essential for us and our planet as it sustains the stability of our ecosystems, provides vital materials and food to us and supports many ecosystem services.

Novel entities may pose risks to humans and the environment. The small particle size and relatively large surface area of micro- and nanoparticles (MNPs) make them capable of adsorbing other novel entities, leading to the formation of aggregated contamination.

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.

Als gevolg van de grote technologische vooruitgang in de gezondheidszorg worden in toenemende mate gegevens verzameld tijdens de uitvoering van klinische onderzoeken.

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.

Promotor: E. Gittenberger, Co-promotores: B.W. Hoeksema; L.P. van Ofwegen