RU Research Fund

Ph.D Student Grants from RU Research Fund 2022

RU Research Fund has awarded 7 new Ph.D. Student Grants. The total amount awarded to new projects is 43.629.600 ISK. The Fund received 11 new applications. Below are information on new projects receiving grants from the Fund 2022. Each grant is 494.400 ISK per month (salaries) for one year + max 300.000 ISK travel grant. Besides new projects funded 2022, 7 projects will receive continuous grant (2nd or 3d year). The total amount granted to continuous projects is 43.629.600 ISK. 

The Fund also granted 7 doctoral students a special grant, who´s research work has been delayed by COVID-19. The special grant is only salaries for max 6 months. The total amount awarded to these special COVID-19 grants is 20.764.800 ISK. Hence the total amount allocated 2022 is 108.024.000 ISK.


Grants 2022

Grants to new projects 2022

1. Applicant: Giulio Mori

  • Department: Dept. of Computer Science
  • Doctoral Student: Giulio Mori
  • Supervisor: David James Thue, Stephan Schiffel
  • Project title: Platform for the Evaluation of Experience Managers

Short description of the project: Experience Management is a field of study that uses AI technologies to improve people's experiences within an Interactive application by changing the environment while the experience is underway. For example, an experience manager within an app for sightseeing can adjust the suggested path to visit an attraction based on how many people are currently visiting a specific spot to improve the overall experience. To date, researchers have created many AI managers to enhance a wide range of experiences in contexts such as education, storytelling, and games. However, this field suffers from a fragmentation problem, where two fundamental issues are impairing new progress: (i) there is no general way to express experience management tasks, and (ii) there is no common platform for evaluation and comparison. With my work, I plan to address these deficiencies by creating a communication protocol that researchers can use to represent experience management tasks and a comprehensive platform for evaluating and comparing different experience managers.

2. Applicant: Sævar Már Gústavsson

  • Department: Dept. of Psychology
  • Doctoral Student: Sævar Már Gústavsson
  • Supervisor: Paul M. Salkovskis, Jón F Sigurðsson
  • Project title: Cognitive analysis of threat beliefs and safety-seeking behaviours in generalised anxiety disorder

Short description of the project: Generalised anxiety disorder (GAD) is a common and disabling mental disorder characterised by excessive and uncontrollable worries. Cognitive behavioural therapy (CBT) has been found to be effective for treating GAD. However, it is less effective than for other anxiety disorders, such as social anxiety disorder or post-traumatic stress disorder. While treatment efficacy of CBT for anxiety disorders has increased over the past three decades, treatment improvement for GAD has stayed relatively the same. Effective cognitive-behavioural understanding of specific anxiety disorders typically involves the identification of idiosyncratic threat beliefs and safety-seeking behaviours (SSB). In all anxiety disorders, with the single exception of GAD, such beliefs and accompanying behaviours are now well understood. The aim of the project is thus to improve the understanding of the range and focus of threat beliefs and SSBs in GAD to inform improvements in treatment of GAD. The research hypotheses of the proposed project are: 1) patients diagnosed with GAD typically focus on threat beliefs which result in their engaging in a range of SSBs that in turn maintain those exaggerated threat beliefs (Study 1 and 2), and 2) that targeting these specific threat beliefs and SSBs will lead to reduction in excessive worry, the cardinal symptom of GAD, and thus will be accompanied by clinical improvement (Study 3).

3. Applicant: Elli Anastasiadi

  • Department: Dept. of Computer Science
  • Doctoral Student: Elli Anastasiadi
  • Supervisor: Luca Aceto, Anna Ingólfsdóttir
  • Project title: Runtime and Equational Verification of Concurrent Programs

Short description of the project: Most modern software is designed or forced to run concurrently with other programs because of the significant increase in efficiency that concurrency offers. However, the complexity of such systems also increases – something that leads to costly and dangerous errors - and verification procedures become more expensive. Additionally, such procedures, when conducted manually, are also prone to human error. Formal verification uses mathematics to analyse systems and therefore removes the latter weakness. We study the underpinnings of two techniques for formally verifying concurrent systems. Concurrency here is modelled through process algebras, and so our initial approach is through equational logic, which is a classic method for analysing such systems. Here, we search for equational axiomatizations for Milner's Calculus of Communicating Systems (CCS) modulo weak bisimilarity, which is a crucial notion of equivalence between processes underlying their formal verification in the presence of internal computational steps. Second, we study which temporal logics can express specifications for concurrent systems and focus on finding which properties of these logics can be checked at runtime. We finally aim to automate the synthesis of the detection-at-runtime mechanism in order to completely eradicate human error. This project's results will impact both research communities and lead to an increase in the capabilities of formal verification techniques in the field of concurrent programs.

4. Applicant: Snæfríður Guðmundsdóttir

  • Department: Sálfræðideild/Dept. of Psychology
  • Doctoral Student: Snæfríður Guðmundsdóttir
  • Supervisor: Heiðdís B. Valdimarsdóttir, Birna Baldursdóttir
  • Project title: Cognitive Impairment Prior to Breast Cancer Surgery and the Impact of Bright Light Therapy on Cognitive Function Following Surgery

Short description of the project: Cancer-related cognitive impairment (CRCI) is one of the most common and feared side effect of breast cancer (BC). Previous studies have mostly focused on the effects of chemotherapy on CRCI, even though evidence suggests it can occur before cancer treatment. Surgery can also cause circadian rhythm (CR) desynchronization, which may contribute to CRCI. Since CRCI is common and has a wide range of negative consequences there is a growing demand for the treatment of CRCI. Bright Light Therapy (BLT) is a low patient burden and low-cost intervention that has been shown to protect BC patients from CR desynchronization and to increase cognitive functioning in other populations. The current study will recruit 160 pairs of BC patients and healthy controls (HC) to assess objective and subjective cognitive function, sleep quality, CR (via actigraphy), fatigue, depression and anxiety. The following research questions will be addressed in three studies: 1) Whether BC patients have cognitive impairment before any BC treatment compared to HC and whether it is associated with more CR desynchronization and higher levels of sleep disturbances. 2) Whether surgery affects CRCI (compared to HC) and if it is associated with more CR desynchronization. 3) Whether circadian stimulating light influences CRCI post-surgery compared to the noncircadian stimulating light. This will be the first study to test the efficacy of BLT on CRCI.

5. Applicant: Rachel Elizabeth Brophy

  • Department: Verkfræðideild/Dept. of Engineering
  • Doctoral Student: Rachel Elizabeth Brophy
  • Supervisor: Andrei Manolescu, Halldór Guðfinnur Svavarsson
  • Project title: Atomistic studies for organo-halide materials for photovoltaics/Integrated Geothermal Power Plant and Eco-Industrial Park – Advanced physics-based and data-driven methods for increasing operational efficiency

Short description of the project: Halide perovskites are new and very promising materials for solar cells, cheaper than silicon, and with a remarkable photoconversion efficiency of about 20\%. The most common of them is the CH$_3$NH$_3$PbI$_3$ (methylammonium lead halide), also known as MAPI. However, under working conditions MAPI tends to break down over time much faster than others. The main reason for the degradation is the iodine dislocation and migration inside the material. In the present project the ionic motion in a perovskite material will be studied using molecular dynamics (MD) computer simulations. The goal is to understand the conditions when the ionic migration occurs and how the resulting electric charge accumulates. Then, several solutions for increasing the stability of the material will be tested by further simulations: changing the organic molecules, changing the halogen, including additional metallic elements in the cell structure, and others. In the 3-rd year of the project, following the results of the MD simulations, experimental fabrication of perovskite solar cell will be conducted using the most promising and feasible design which will optimize the device efficiency and stability.

6. Applicant: Óskar Sigþórsson

  • Department: Verkfræðideild/Dept. of Engineering
  • Doctoral Student: Óskar Sigþórsson
  • Supervisor: Brian Elmegaard, Torben Schmidt Ommen, María Sigríður Guðjónsdóttir, Guðrún Arnbjörg Sævarsdóttir
  • Project title: Integrated Geothermal Power Plant and Eco-Industrial Park – Advanced physics-based and data-driven methods for increasing operational efficiency

Short description of the project: The share of renewable energy needs to be increased to reduce the effects of climate change. One of the options to achieve this is to exploit further geothermal energy. Using geothermal energy for electrical power production is a challenging task, in terms of technical and financial feasibility. Minerals and non-condensable gases are dissolved in the geothermal fluid, causing scaling and corrosive conditions. It is thus highly important to monitor performance of the power plant. Coupling the geothermal power plant with an eco-industrial park, resource streams from the power plant that otherwise are unused can be used. Optimising the use of resource streams from geothermal power plants and among the industries within the ecoindustrial park is therefore highly relevant. This PhD project aims to introduce novel methods for energy monitoring and process integration to the geothermal power plant industry. The general hypothesis is the following: The use of the energy resource in a geothermal power plant and its eco-industrial park can be used more efficiently. This is followed by two sub-hypotheses: 1) The geothermal energy resource can be used more efficiently in the ecoindustrial park by a detailed understanding of sources of inefficiencies and 2) Operation of the geothermal power plant can be improved, with further insights into the operation and also with better ways to monitor the operation and hereby identify equipment faults and measuring their effects.

7. Applicant: Lilja Guðrún Jóhannsdóttir

  • Department: Tölvunarfræðideild/Dept. of Computer Science
  • Doctoral Student: Lilja Guðrún Jóhannsdóttir
  • Supervisor: Anna Sigríður Islind, María Óskarsdóttir, Þrúður Gunnarsdóttir
  • Project title: Digital nudging to increase patient engagement in a self-management platform

Short description of the project: Unhealthy lifestyle choices can develop into chronic diseases that constitute one of the most significant causes of premature death. Self-management platforms (SMPs) inform and assist patients suffering from chronic diseases in making healthier lifestyle choices. However, poor engagement in SMPs can limit the potential benefit they bring to patients. Incorporating digital nudges that derive from behavioural economics and psychology into the design features of an SMP may improve engagement and influence patients' choices towards health-improving behaviour. This project aims to 1) create digital nudges that drive traffic into the SMP, 2) encourage patients to spend more time in the SMP, and 3) cross-validate the results with activity data from smartwatches to see whether changes in behaviour are detected. We expect the digital nudges to improve the engagement with the SMP, which will lead to health-improving behaviour by patients suffering from chronic diseases.

Continuous grants 2022

Applicant Project title Department Doctoral student
Arash Sheikhlar Causal Knowledge Transfer via Non-Axiomatic Reasoning Tölvunarfræðideild/Dept. of Computer Science Arash Sheikhlar
Halldór Guðfinnur Svavarsson Piezoresistance of silicon-nanowire arrays Verkfræðideild/Dept. of Engineering Elham Aghabalaei Fakhri
Kristinn Torfason Properties of Electron Beams from Microstructured Emitters Verkfræðideild/Dept. of Engineering Yuan Zhou
Paolo Gargiulo Quantifying postural control and motion sickness assessing biosignals during virtual reality simulation Verkfræðideild/Dept. of Engineering Deborah Cecelia Rose Jacob
Maxime Elliott Tullio Segal Designing Capital Ratio Triggers for Contingent Convertibles Verkfræðideild/Dept. of Engineering Maxime Elliott Tullio Segal
Björn Jón Bragason The Office of the Head of State in Iceland from the founding of The Kingdom of Iceland in 1918 until present days Lagadeild/Dept. of Law Björn Jón Bragason
Illugi Torfason Hjaltalín Artificial Intelligence in the 21st Century: Developing, Implementing and Deploying AI in Iceland's Public Sector Viðskiptadeild/Dept. of Business Administration Illugi Torfason Hjaltalín

COVID-19 grants 2022

Applicant Project title Department Doctoral student
Émile Nadeau Extending the Combex framework Tölvunarfræðideild/Dept. of Computer Science Émile Nadeau
Hlín Kristbergsdóttir Psychosocial risk factors for childbirth interventions and neonatal outcomes Sálfræðideild/Dept. of Psycholoy Hlín Kristbergsdóttir
Marco Recenti Assessment, diagnostics and prediction models to advance digital health Verkfræðideild/Dept. of Engineering Marco Recenti
Duncan Paul Attard Ensuring Correctness in Distributed Systems Tölvunarfræðideild/Dept. of Computer Science Duncan Paul Attard
Sigurður Ingi Erlingsson Analytical results for Shubnikov-de Haas oscillations in a two-dimensonal electron gas with spin-orbit and Zeeman coupling Verkfræðideild/Dept. of Engineering Hamed Gramizedeh
Magnus de Witt Sustainable Energy Supply in Unconnected Arctic Areas: Analysis of resources, technology and policies for designing energy systems Verkfræðideild/Dept. of Engineering Magnus de Witt
Heiðdís B. Valdimarsdóttir Áhrif ljósameðferðar á krabbameinstengda þreytu hjá konum með brjóstakrabbamein Sálfræðideild/Dept. of Psycholoy Huldís Franksdóttir Daly


Grants 2019

RU Research Fund has awarded 8 PhD Student Grants og the total amount 42.720.000 ISK. Each grant is 420.000 ISK per month for max one year + 300.000 ISK travel grant.

Furthermore, RU has launched a special two-semester course for PhD students. The course addresses the following topics: How to write a good grant proposal to a competitive research fund, how to write and publish a scientific paper and write scientific English, ethics in science, statistical methods in science – best practice (field specific), and Instruction how to teach. Instructors are Dr. Kristján Kristjánsson, Director of RU Research Services and Dr. Rannveig S. Sigurvinsdóttir, Assistant Professor at School of Business, Psychology Department.

Ármann Gylfason: Lagrangian dispersion in mixed convective turbulence

Grant amount: 5.340.000 ISK

School: School of Science and Engineering

Doctoral Student: NN

Supervisor: Ármann Gylfason

Project title: Dreifni agna í blönduðu varmadrifnu iðustreymi

Short description of the project:

The goal of the project is to explore the transport properties of turbulent thermal convection by a detailed investigation of the Lagrangian properties of Rayleigh-Bénard convection and mixed convective flow systems where the thermal field is perturbed by mechanical forcing of turbulence. We will perform Lagrangian measurements of passive tracers and their temperature and inertial particles, both near solid boundaries and in the bulk flow. Our focus is on the coherent thermal plume structures of the buoyant field, and implications on passive and inertial particle dynamics, dispersion, and distribution of particles, heat and substances. Experiments will be performed in Laboratories at Reykjavik University and at CNRS ENS de Lyon. We apply Lagrangian Particle Tracking combined with Eulerian measurements of the velocity and temperature fields. In addition, we will develop a new Mie Scattering Imaging method, to simultaneously detect Lagrangian particle temperature and velocity, by measuring changes in the size of expanding polymer microcapsules.

The focus of the proposal lies in systematic adjustment of flow parameters, ranging from buoyancy driven flows to perturbations of isotropic flows. The results will be useful to the study of turbulence involving convection, occurring widely in natural and engineering flows. The results will provide a new perspective on convective turbulence and give us insight into deterministic and probabilistic structures that signifies turbulence.

Duncan Paul Attard: Ensuring Correctness in Distributed Systems

Grant amount: 5.340.000 ISK

School: School of Computer Science

Doctoral Student: Duncan Pal Attard

Supervisor: Adrian Francalanza (University of Malta)

Short description of the project:

Runtime Verification is becoming a widespread software verification technique used in cases where the model of the system under scrutiny is unavailable or infeasible to obtain. The technique perceives the system as a black box and can be used for post-deployment verification or in scenarios were system components are loaded dynamically. However, runtime verification has severe limits in terms of what can be monitored at runtime since its analysis is restricted to the current execution trace. We propose to investigate novel methods for extending these limits. In particular, we consider methods that rely on software replication to increase the runtime information available for analysis: multiple traces obtained via the observed execution of each system replica are exploited to obtain a more comprehensive view of system behaviour. Software replication arises naturally in distributed settings where systems typically consist of multiple components, making this an ideal area where our proposed research can be extensively applied.

Gylfi Þór Guðmundsson: The use cases of Anomaly Detection in Aerial Images

Grant amount: 5.340.000 ISK

School: School of Computer Science

Doctoral Student: NN

Supervisor: Gylfi Þór Guðmundsson

Short description of the project:

The use of autonomous unmanned aerial vehicles (UAV) is already growing into a blooming business

and is expected to grow to a revenue of 10 billion Euros in Europe by 2035. The UAV's fulfil a wide range of services but the primary sensing devices of the UAV is the video camera and imaging. Image processing is therefore an important research area in maximising the utility of the UAV revolution. The current state-of-the-art in almost all image processing is Deep-Learning (DL) but the DL algorithms are computationally demanding and thus require power-hungry hardware. For UAV's, where battery power is a scares resource, this is a serious issue and why the image processing is typically done post flight (off-line). The ability to do on-line image processing can however be of great benefit, both in regards to developing new types of applications and services but also in improving the current applications of the drones. We propose here a project with two primary goals: 1) The development of Anomaly Detection in aerial imagery and demonstrate how useful that ability is to solve a wide range of tasks; and 2) The adaptation and extensive evaluation of applying our software to state-of-the-art mobile graphical processing units (GPU) that can do the processing on-line.

Henning Arnór Úlfarsson: Combinatorial Exploration with Applications to Permutation Patterns and other Structures

Grant amount: 5.340.000 ISK

School: School of Computer Science

Doctoral Student: NN

Supervisor: Henning Arnór Úlfarsson

Short description of the project:

We propose to continue the development of a framework that can leverage domain-specific knowledge to discover and automatically prove theorems in several areas of mathematics. Combinatorial exploration is an experimental approach that rigorously derives structural results about mathematical objects. When a human has discovered the structure of an object, there are several tools which allow various properties of the object to be computed. However, the steps from the problem statement to the structure is often ad-hoc. This is the gap we propose to fill.

Using techniques from enumerative and analytic combinatorics, computer algebra, and algebraic geometry, we have implemented a prototype of our framework. By adding domain-specific knowledge from the field of permutation patterns to the prototype, we created an algorithm that has discovered new theorems and rediscovered results spanning dozens of papers in the literature.

We propose to integrate techniques from machine learning to enhance the prototype, as well as turning the output into a formal proof. We will allow the researcher to interact with the framework while running through a graphical user interface. Finally, we propose to add more strategies for reasoning about several combinatorial objects.

The outcome of this proposal training of young researchers, and publications in journals and presentations at international conferences. The implementations of these theoretical algorithms will be made available open source.

Kamilla Rún Jóhannsdóttir: Assessment of cognitive workload by understanding the heart's neurophysiology

Grant amount: 5.340.000 ISK

School: School of Business

Doctoral Student: NN

Supervisor: Kamilla Rún Jóhannsdóttir

Short description of the project:

Managing cognitive workload effectively is critical for many real world operational environments such as the cockpit or the automobile. Workload monitoring is most commonly done by measuring cardiovascular reactivity. However, our understanding of the psycho-physiological factors controlling the heart‘s reactivity to workload is limited, hindering us in moving forward to a reliable and meaningful measure of cognitive workload. The objective of the proposed research is to understand how cognitive workload as handled by the individual is reflected in the heart's reactivity by looking further at the temporal nature of the signal, individual differences, and the brain. The temporal nature of the cardiovascular signal will be captured using time- and frequency domain methods thereby reducing the use of averaging over time segments and matched against the relevant individual trait dimensions. Additional empirical work will be carried out to further understand the complex interaction between brain and peripheral physiology in regulating the heart‘s state. The ultimate goal of the proposed project is to model the heart‘s reaction to cognitive workload, taking into consideration the brains input and personality trait characteristics.

Mohammad Adnan Hamdaqa: A Framework for Building Secure and Reliable Proof-Carrying Blockchain Applications

Grant amount: 5.340.000 ISK

School: School of Computer Science

Doctoral Student: NN

Supervisor: Mohammad Adnan Hamdaqa

Project title: A Framework for Building Secure and Reliable Proof-Carrying Blockchain Applications

Short description of the project:

The goal of this project is to improve trust in blockchain technologies by filling the gap between smart contract developers and consumers. The project aims to facilitate the development of smart contracts by providing a high-level language on top of current smart contract frameworks. The proposed language is more abstract than existing smart contract specification languages (e.g., Solidity, Viper, or Serpent). It will help software developers architect and build blockchain applications, and generate target executable contracts with the accompanying safety and reliability proofs that will satisfy consumers' safety policies.

The project will take a model-driven engineering approach to develop a modelling language for smart contracts that is platform agnostic. Unlike any other model-driven code generator, our proposed code generation approach will employ a proof carrying code (PCC) mechanism that will enable us to automatically generate proofs of safety and attach certificates to the smart contract code, in order to enable any of the blockchain platforms to verify the smart contract code prior to its deployment.

Slawomir Marcin Koziel: Design-Oriented Computationally-Efficient Surrogate Modelling of High-Frequency Structures

Grant amount: 5.340.000 ISK

School: School of Science and Engineering

Doctoral Student: NN

Supervisor: Slawomir Marcin Koziel

Short description of the project:

Accurate evaluation of the system performance is a fundamental prerequisite to ensure reliability of design processes in any engineering discipline. In the design of high-frequency structures (RF/microwave circuits, antennas and antenna arrays, photonics, electromagnetic compatibility, etc.) it is normally performed using full-wave electromagnetic (EM) analysis, which is inherently expensive in computational terms when applied to realistic structures. Consequently, its straightforward application in design and modelling processes is challenging, especially when repeated simulations at different points of the design/modelling space are necessary, e.g., for parametric optimization, statistical analysis, robust or tolerance-aware design. For these tasks, fast yet reliable replacement models are indispensable. The majority of existing methods for constructing of replacement models, data-driven and surrogate-assisted, are of limited applicability in terms of dimensionality and ranges of parameter spaces. This research project aims at development of techniques for low-cost construction of fast surrogate models which can be utilized for real-world design and performance analysis tasks of RF, microwave, antenna, and photonic engineering, and closely related fields, e.g., high-frequency electronics, EM packaging, RFID, digital signalling, wireless powering.

Slawomir Marcin Koziel: Accelerated Surrogate-Assisted Design of High-Performance Microstrip Corporate Feeds Integrated with Array Apertures

Grant amount: 5.340.000 ISK

School: School of Science and Engineering

Doctoral Student: NN

Supervisor: Slawomir Marcin Koziel

Short description of the project:

Integration of devices, components, and modules is essential for miniaturization of modern electronics. At the digital end, integration is realized with semiconductor technology. For integrated antenna-feed modules at the high-frequency end of radars, communication, navigation, RFID, and medical systems, CAD tools and techniques (in addition to devices and materials) are essential for development. Microstrip antenna arrays are an important class of low-profile/-weight/-cost and embeddable antennas of spatial filtering/directive capabilities. Microstrip corporate feeds allow for better control of microwave signals and extendable for phased and reconfigurable solutions. Systematic, man-hour efficient design approaches have not been developed yet for integrated high performance array modules—contemporary antenna engineering means used in practice are not readily suitable for integrated microstrip arrays. This project aims reliable, comprehensive, computationally-efficient, and automated techniques (from prototyping stage up to validation) for design of low-sidelobe microstrip antenna arrays with integrated apertures and feeds.

Grants 2018

RU Research Fund has awarded 8 Ph.D. Student Grants. The total amount awarded is 42.720.000 ISK. The Fund received 9 applications. Below are information on the projects that receive grants from the Fund 2018. Each grant is 420.000 ISK salary support per month for max one year + 300.000 ISK travel grant.

List of RU Research Fund Projects:


Hlín Kristbergsdóttir

  • Grant amount: 5.340.000 ISK
  • Applicant: Hlín Kristbergsdóttir
  • School: School of Business
  • Supervisor: Jón F. Sigurðsson and Heiðdís B. Valdimarsdóttir
  • Project title: Impact of mental distress during pregnancy on child adverse outcomes
  • Short description of the project:
    Untreated mental illness during pregnancy is a serious problem affecting up to 20% of women during the perinatal period. This major public health issue impacts not only the mothers but their future children's health, emotional and cognitive development. Research on the association between perinatal distress and adverse child outcomes is limited (e.g. lack of diagnosis and distinguish between level of distress).

    The aim of this project is to examine impact of severity of prenatal mental distress on children's adverse outcomes at the age of 0-13 years and to explore potential moderators of this relationship. Data will be obtained from 437 children of mothers that were screened with symptoms of distress, diagnosed with major depression and/or anxiety disorder or found to be healthy. To test path models we will use latent growth trajectories models.

    We hypothesise that children exposed to prenatal distress are a) different at birth b) have different developmental history c) worse academic performances d) are more likely to show conduct and emotional problems than children not exposed. Also, that children born to mothers diagnosed with a mental disorder will have the worst outcomes.

    Further, that higher level of distress, single mothers, poverty and low maternal education will moderate the relationship. The results will have both theoretical and applied implications providing information on high risk children and beneficial for improving preventive measures in antenatal care.

María Kristín Jónsdóttir

  • Grant amount: 5.340.000 ISK
  • Applicant: María Kristín Jónsdóttir
  • School: School of Business
  • Doctoral Student: Ingunn S. Unnsteinsdóttir
  • Supervisor: María Kristín Jónsdóttir
  • Project title: Concussions among Icelandic athletes: Incidence, hypopituitarism and psychological health
  • Short description of the project:
    Study 1:
    This is a 12-month prospective study of concussions among male and female elite athletes in Iceland. Concussions represent a public health crisis and athletes are at a risk for repeated concussions. Sport injury rates are not uniform across cultures and national information on concussion incidence are needed. Incidence will be reported as number of concussion divided by athlete-exposure (AE) and reported by age, gender, sport, position played, and whether the concussion happened during practice or in a game.

    Study 2: Hypopituitarism (i.e., deficient pituitary functioning) and its relationship to concussion history, neuropsychology/IQ , mental health and quality of life in concussed female elite athletes will be studied. Published findings show that hypopituitarism is common in concussed athletes but only include data on seven female athletes. Yet, females are often said to be particularly vulnerable to concussions.

    There are three phases to this study: 1) a questionnaire will be sent to all Icelandic female elite athletes, active and retired (aged 18-45, N = 1160), in high concussion-risk sports. We will ask about concussion history, mental health/quality of life and concussion symptoms; 2) those with a self-reported history of concussion go to phase 2, which includes a more precise assessment of concussion history, IQ and neuropsychological testing. In phase 3, those with a clear history of concussion undergo hormone evaluation and a medical exam.

Luca Aceto


  • Grant amount: 5.340.000 ISK
  • Applicant: Luca Aceto
  • School: School of Computer Science
  • Doctoral Student: NN
  • Supervisor: Luca Aceto and Anna Ingólfsdóttir
  • Project title: Open Problems in the Equational Logic of Processes (OPEL)
  • Short description of the project:
    The overarching goal of this project is to solve some of the challenging open problems in the equational axiomatisation of behavioural equivalences over process calculi. The results obtained within this project will lead to an improved understanding of the power of the classic logic of equations in describing and reasoning about a ubiquitous class of computing systems, and will have impact on future work on algebraic methods in concurrency theory. The project will be the first one in concurrency theory (and perhaps in computer science as a whole) that uses large-scale on-line collaboration to solve problems in that field, thus providing a blueprint for future research cooperation.

Sigrún Ólafsdóttir

  • Grant amount: 5.340.000 ISK
  • Applicant: Sigrún Ólafsdóttir
  • School: School of Business
  • Supervisor: Jón F. Sigurðsson and Paul Salkovskis
  • Project title: Development and evaluation of a cognitive behavioural treatment for persistent physical symptoms that cause work disability
  • Short description of the project:
    Background: Persistent physical symptoms (PPS) that cannot be explained by organic diseases are common in all health care settings and have been associated with diminished quality of life, increased work disability and high health care use and cost. Conventional medical therapy is largely ineffective.

    There is evidence for a range of Cognitive-Behavioural treatments (CBT) but those are based on models that are specific to particular types of PPS which creates serious practical problems. Recently, we addressed these problems with a transdiagnostic cognitive behavioural model for PPS and novel hybrid transdiagnostic CBT (HT-CBT). Aims: To adapt the HT-CBT for PPS causing work disability and evaluate in a Randomised Controlled Trial comparing HTCBT to treatment as usual, analysing data using the intention to treat method. Participants will be 250 people with PPS seeking work rehabilitation from VIRK Vocational Rehabilitation Fund. Feasibility: We are cooperating with VIRK and pilot data shows that severe PPS are common among VIRK clients and they generally find psychological treatment acceptable. Originality and impact: The study adds considerably to existing knowledge as it responds to poor availability of cost-effective treatments for PPS and a clear need for a treatment suitable for work rehabilitation. If effective, the HT-CBT will have major public health implications as it will be manualized, easy to deliver and be more cost-effective than currently available treatments.

Hulda Kristín Magnúsdóttir

  • Grant amount: 5.340.000 ISK
  • Applicant: Hulda Kristín Magnúsdóttir
  • School: School of Law
  • Supervisor: Gunnar Þór Pétursson
  • Project title: Extending the borders of the Energy Union - the effects on Icelandic energy legislation
  • Short description of the project:
    Agreement on energy legislation in Iceland has been and still is underestimated, with a focus on the reservation made in Article 125 of the EEA Agreement in relation to property rights. I have divided my research into the following research questions: (I) What is the current scope of EEA energy law and how has it evolved since 1994? (II) How has EEA energy law and the provisions on free movement in the EEA Agreement impacted energy legislation in Iceland, in particular with reference to property rights? (III) To what degree have Iceland and Norway managed to modify EU energy law to their standpoint upon incorporation into the EEA Agreement and what were the underlying factors for the standpoint adopted by Iceland/Norway? (IV) What are the potential effects of the Energy Union on EEA energy law? To answer these research questions, I will be using legal dogmatics as an established research method in law to answer questions I, II and IV. To be able to answer question III, I will use a comparative socio-legal approach where I will be using quantitative research methods to determine what factors have impacted the standpoint adopted by Iceland and Norway.

    My research will provide a detailed insight into how Iceland and Norway have sought to protect their national interest and maintain their competitive edge, particularly in comparison to EU Member States in relation to energy.

Sigurður Ingi Erlingsson

  • Grant amount: 5.340.000 ISK
  • Applicant: Sigurður Ingi Erlingsson
  • School: School of Science and Engineering
  • Doctoral Student: NN
  • Supervisor: Sigurður Ingi Erlingsson
  • Project title: Analytical results for Shubnikov-de Haas oscillations in a two-dimensonal electron gas with spin-orbit and Zeeman coupling
  • Short description of the project:
    Here we derive an analytical expression for the Shubnikov-de-Haas (SdH) oscillations in a two-dimensional electron gas with both Rashba and Dresselhaus spin-orbit interactions of arbitrary strength in the presence of Zeeman coupling. We first obtain accurate approximate spin-split Landaulevel eigenenergies and from these an exact trace formula for the density of states, which is directly connected to the magnetoresisitivity of the system. Our analytical results hold for a wide range of Rashba and Dresselhaus couplings and agree well with the numerical calculations, even for very high Landau level index. This allows us to analytically describe SdH oscillations and make predictions on how the Zeeman coupling modifies the condition for the absence of beatings.

    We propose how our method can be used to improve the analysis of existing experimental data for semiconductors with strong spin-orbit coupling.

Andrei Manolescu 

  • Grant amount: 5.340.000 ISK
  • Applicant: Andrei Manolescu
  • School: School of Science and Engineering
  • Doctoral Student: NN
  • Supervisor: Andrei Manolescu and Sigurður Ingi Erlingsson
  • Project title: Thermoelectric transport in core/shell nanowires
  • Short description of the project:
    In this proposal, we describe our intended research on the thermoelectric and heat transport characteristics of semiconductor core/shell nanowires, beyond the linear regime, by computational methods. The cross section of such a nanowire can de circular or polygonal. We shall study the effect of the nanowire shape and length on the thermoelectric transport. We shall investigate the possibilities to control the thermoelectric efficiency with magnetic or electric fields, for specific geometries, and for specific temperature domains.

Andrei Manolescu 

  • Grant amount: 5.340.000 ISK
  • Applicant: Andrei Manolescu
  • School: School of Science and Engineering
  • Doctoral Student: NN
  • Supervisor: Andrei Manolescu
  • Project title: Majorana states in core/shell nanowires
  • Short description of the project:
    Majorana states are quasiparticles which can be created in nanosystems, reminding of the elementary particles with the same name predicted in 1937. Model calculations predicted that such states can be obtained at the two ends of a semiconductor nanowire in an induced superconducting state and recent experimental investigations gave some hints on their existence. Core/shell nanowires are radial heterostructures with polygonal cross section, i.e. prismatic, very interesting for Majorana physics. Electrons with low energy can be localized at the corners (edges) and can create multiple Majorana states at each nanowire end.

    The goal of the present research proposal is to investigate, by theoretical and computational means, the implications of the core/shell prismatic geometry on the Majorana states.


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