RU Research Fund

SUBMISSION DEADLINE IS 30th OF JANUARY 2023

Ph.D Student Grants from RU Research Fund 2023

RU Research Fund has awarded 12 new Ph.D. Student Grants. The total amount awarded to new projects is 77.040.000 ISK. The Fund received 22 new applications. Below is information on new projects receiving grants from the Fund 2023. Each grant is 510.000 ISK per month (salaries + salary-related costs) for one year + a max 300.000 ISK travel grant. Besides new projects funded in 2023, 7 projects will receive a continuous grant (2nd or 3rd year). The total amount granted to continuous projects is 44.940.000 ISK. The Fund also granted a special travel grant to 3 doctoral students, who do not have a research grant, amount of 900.000 ISK. Hence the total amount allocated 2023 is 122.880.000 ISK.

Grants 2023

1.

• Umsækjandi / Applicant: Medy Dervovic
• Deild / Department: Lagadeild/Department of Law
• Doktorsnemi / Doctoral Student: Medy Dervovic
• Leiðbeinandi / Supervisor: Snjólaug Árnadóttir/Bjarni Már Magnússon
• Heiti verkefnis / Project title: Lagaleg áhrif loftslagsbreytinga á hafrétt á norðurslóðum/Normative Impact of Climate Change on the Law of the Sea in the Arctic

Short description of the project:  
As climate change accelerates, the Arctic Ocean undergoes profound transformations primarily manifested by sea-ice coverage reduction, sea-level rise, coastal erosion, warming temperatures, and ocean acidification. Paradoxically, the opening-up of the Arctic Ocean unveils economic prospects in the realm of shipping, offshore resource extraction, fishing, and tourism activities. In line with these environmental changes and economic development pressures, this project endeavors to offer the first comprehensive assessment of the normative impact of climate change on the law of the sea in the Arctic. Building on the preliminary identification of adverse climatic changes in the Arctic Ocean, this project will emphasize legal challenges faced by the 1982 United Nations Convention on the Law of the Sea (UNCLOS) and discuss their practical consequences for Arctic navigation, environmental protection, and maritime boundaries. It will also address the adaptive capacities of UNCLOS vis-à-vis climate change and analyze emerging international and regional legal instruments as tools reinforcing the relevance and effectiveness of the law of the sea in a rapidly changing Arctic. This project will resort to treaty interpretation and an extensive review of academic literature and jurisprudence to provide law/policymakers and scholars with appropriate mechanisms to adapt to potential and proven difficulties caused by climate change affecting the correct implementation of UNCLOS in the Arctic.

2.

• Umsækjandi / Applicant: Grischa Liebel
• Deild / Department: Tölvunarfræðideild/Department of Computer Science
• Doktorsnemi / Doctoral Student: NN
• Leiðbeinandi / Supervisor: Grischa Liebel
• Heiti verkefnis / Project title: Bætt þátttökuskilyrði í hugbúnaðarþróun og tengdri menntun fyrir taugsegin einstaklinga/Towards Inclusion of Neurodivergent Individuals in Software Engineering Education and Practice

Short description of the project:
Neurodiversity is an umbrella term describing variations in brain function among individuals, including for example common conditions such as autism spectrum disorder, attention deficit hyperactivity disorder, or dyslexia. Neurodivergent individuals (NDI) often struggle in higher education and on the job market, e.g., due to difficulties or differences in communication, reading or writing difficulties, or reduced attention span. However, NDI also commonly possess strengths compared to neurotypical individuals, such as better memory or creativity. While the software engineering (SE) industry matches common interest profiles of NDI, there is only little understanding of the experiences NDI have in SE. Therefore, this project aims to improve inclusion of NDI in SE by (a) increasing the understanding of challenges and strengths of NDI in SE education and practice and (b) proposing and evaluating suitable interventions to target these. We work in close collaboration with experienced partners in research, education, and society, following a participatory research approach, i.e., involving NDI at all project stages. The project aims to improve inclusion of NDI in SE education and practice, and to increase awareness among stakeholders in the field, as well as society as a whole.

3.

• Umsækjandi / Applicant: Jón Friðrik Daðason
• Deild / Department: Tölvunarfræðideild/Department of Computer Science
• Doktorsnemi / Doctoral Student: Jón Friðrik Daðason
• Leiðbeinandi / Supervisor: Hrafn Loftsson
• Heiti verkefnis / Project title: Mállíkön fyrir tungumál með takmörkuðum málföngum/Language Representation Models for Low and Medium-Resource Languages

Short description of the project:
The Transformer is a recently proposed neural network architecture which has obtained state-of-the-art results on a wide variety of natural language processing (NLP) tasks, such as question answering, sentiment analysis and automatic text summarization. It has many benefits over previous architectures, the most significant of which may be its scalability. Larger models are more effective at solving complex problems, but are also more costly to train. The size of the largest Transformer-based model has grown from 110 million parameters in 2018 to 1.6 trillion parameters in 2021. Training datasets have grown similarly in size, further improving the performance of the models. The largest training dataset for English has grown from 800 million words to 1.4 trillion words over the same time period. More research is needed into how these models can best be utilized for low and medium-resource languages, where training data is scarce and computational resources are limited. We will evaluate the data efficiency of various training methods, experiment with how small monolingual training datasets can best be augmented with multilingual or machine-translated text and perform a thorough evaluation of commonly used text filtering techniques.

4.

• Umsækjandi / Applicant: Andrei Manolescu
• Deild / Department: Verkfræðideild/Department of Engineering
• Doktorsnemi / Doctoral Student: NN
• Leiðbeinandi / Supervisor: Andrei Manolescu
• Heiti verkefnis / Project title: Nándarhrif ofurleiðara innan kjarna/skeljar rúmfræði/Proximity superconductivity in core/shell geometry

Short description of the project:
Junctions of semiconductor and superconductor materials have attracted much interest in the last years due to the possibilities they show for quantum computing. In such junctions the superconductivity can penetrate into the semiconductor, a phenomenon called the proximity effect, leading to Andreev bound states, and to topological states if spin-orbit interaction and magnetic fields are present. The main goal of our research proposal is to describe, by theoretical and computational means, the proximity effect in core/shell nanowires, which are made of semiconductor core, partially or totally surrounded by a shell of superconductor metal. These nanowires can have complex geometry, with polygonal cross section, and several gaps in the longitudinal direction, corresponding to multiple junctions. Such nanowires are currently under investigation by two experimental groups from Germany and Japan, our modelling being a cooperative effort to consider their most recent experimental data.

5.

• Umsækjandi / Applicant: Arthurton Travis Elvean Bellot
• Deild / Department: Verkfræðideild/Department of Engineering
• Doktorsnemi / Doctoral Student: Arthurton Travis Elvean Bellot
• Leiðbeinandi / Supervisor: Juliet Ann Newson
• Heiti verkefnis / Project title: Smíði á fræðilega vel grunduðu og notendavænu líkani sem hermir og bestar vinnslu jarðhita á lághitasvæðum/Creating a robust modelling tool for optimizing the use of low-temperature geothermal fields

Short description of the project:
Reservoir modelling plays an essential role in geothermal resource management. The tools represent resource physics, integrate system information, and perform future scenario simulations for the response to exploitation. But reservoir modelling tools require an increasingly specialized workforce and modelling environment, and the ability of a project to support modelling costs is inversely related to value/unit of produced energy. Therefore, low-temperature resource developments have proportionately higher modelling costs. This project addresses this problem by creating a tool for modelling low-temperature resources, that adequately represents the resource, for day-to-day use by company technical staff. The project will use the existing modelling software of LUMPFIT and Waiwera. LUMPFIT is a lumped parameter tool for modelling reservoir pressure changes [1]. Waiwera is an open-source parallelized geothermal flow simulator [2]. In this project a Python script will create simplified Waiwera simulations, resulting in a more accurate hydraulic and thermal reservoir representation than LUMPFIT but limited in their complexity. The work is essentially an investigation of sensitivity to modelling parameters and model discretization, and creation of an optimized combination of these for the most efficient tool. The result provides a better understanding of the production capacity of the system and for the optimization of well placement. Case studies are from Poland and Iceland.

6.

• Umsækjandi / Applicant: Jasmine Xuereb
• Deild / Department: Tölvunarfræðideild/Department of Computer Science
• Doktorsnemi / Doctoral Student: Jasmine Xuereb
• Leiðbeinandi / Supervisor: Adrian Francalanza and Antonios Achilleos
• Heiti verkefnis / Project title: Útvíkkun á takmörkunum sannprófana í rauntíma/Extending the Limits of Runtime Verification

Short description of the project:
Runtime Verification is becoming a widespread software verification technique, especially when the system model is unavailable or not fully understood. However, despite its merits, this technique is limited by the fact that analysis is based on finite fragments of the system run. In this project, we investigate novel approaches for extending these limits. In particular, we consider an alternative runtime verification setup that builds on the classical one and examine its effect on the set of properties that can be checked at runtime. We then investigate how we can further extend the proposed setup to verify properties that describe the expected behaviour of the monitors themselves, especially those relating to security and privacy requirements. The results of this project will impact the reliability of software as it will increase the applicability of runtime verification tools while providing security and privacy assurances.

7.

• Umsækjandi / Applicant: Joshua David Springer
• Deild / Department: Tölvunarfræðideild/Department of Computer Science
• Doktorsnemi / Doctoral Student: Joshua David Springer
• Leiðbeinandi / Supervisor: Marcel Kyas
• Heiti verkefnis / Project title: Nákvæmar Drónalendingar Aðferðir fyrir Sjálfvirkar Rannsóknir á Mars/Precision Drone Landing Methods for Autonomous Mars Exploration

Short description of the project:
Mars exploration is moving towards a paradigm of collaborative drone-rover teams, where the drone flies to hard-to-reach places like solidified lava flows to collect geological samples, then coordinates with the rover to relay its collected data to earth. The NASA-supported RAVEN team tests such missions in Iceland, which has long served as a testing ground for interplanetary exploration because of its otherworldly terrains and weather. The proposer intends to solve the open problem of autonomous drone landing on landing pads and solidified lava flows in Iceland (Holuhraun), in collaboration with RAVEN, for future Mars exploration. The lack of infrastructure on Mars means the drone must have a minimal sensor set (without GPS), and limited computational/power capacity. Such a solution will contribute both to future Mars exploration and to terrestrial drone applications that require GPS-denied precision landing. With embedded computational hardware (TPUs/GPUs), a drone will analyze data from depth cameras and LIDAR sensors in real time. The drone will identify landing pads via visual markers, and safe landing sites in lava flows via topographical terrain analysis with Gaussian process models and deep learning methods (e.g. U-nets and auto-encoders). We will develop such a solution in simulation, then transition to the real world. The proposer has 3 years of experience with drones in Iceland, active collaboration with RAVEN, and experience with the necessary software/hardware.

8.

• Umsækjandi / Applicant: Yasuaki Morita
• Deild / Department: Tölvunarfræðideild/Department of Computer Science
• Doktorsnemi / Doctoral Student: Yasuaki Morita
• Leiðbeinandi / Supervisor: Tarmo Uustalu
• Heiti verkefnis / Project title: Fjölforritunarmála merkingarfræði fyrir Wasm/Multi-Language Semantics for Wasm

Short description of the project:
In modern software development, with the proliferation of cross-language infrastructures such as Wasm and LLVM, it is common for a single program to be associated with multiple programming languages. While the semantics of programming languages is a foundation of formal reasoning of programs, semantics in the presence of multiple languages is far from mature, and the reasoning is hard. This research consists of two parts: 1. Theoretical part: We develop a theory of multi-language semantics. Operational multi-language semantics is an approach that introduces interoperability into different programming languages. We classify interoperability by its effect on the semantics of individual languages and the whole system. 2. Technical part: WebAssembly(Wasm) is a stack-based machine language that runs in most web browsers. We demonstrate several optimization techniques on Wasm with correctness proof. Furthermore, prove (or disprove) the correctness of those optimizations in the presence of different multi-language interoperability. The formalization and proofs will be given in Agda. This research expands the applicability of formal methods and contributes to the safety of Wasm, in turn, the safety of realistic systems such as Web applications.

9.

• Umsækjandi / Applicant: Kevin Matthias Henry
• Deild / Department: Viðskiptadeild/Department of Business Administration
• Doktorsnemi / Doctoral Student: Kevin Matthias Henry
• Leiðbeinandi / Supervisor: Katrín Ólafsdóttir
• Heiti verkefnis / Project title: Áhrif fræðslu um jafnrétti og fjölbreytileika og jafnrétti á jafnrétti allra kynja í skipulagsheildum/Effect of diversity, inclusion and equality (DIE) training on gender equality of all genders in organizations

Short description of the project:
Equal treatment of all genders is still not given in most organizations even nowadays. Many organizations conduct diversity, inclusion and equality (DIE) trainings in order to improve equality among employees. The goal of this proposed research is to examine effects of different types of DIE trainings with regards to their effects on organizational gender equality. This also includes non-binary and transgender equality. Trainings will be analyzed based on a four-dimension model: 1. Personal Dimension, 2. Organizational Dimension, 3. Non-Binary/Trans Dimension and 4. Executive/HR Dimension. Based on those dimensions various training methods will be analyzed and compared with their effects on gender equality in the organization. Specific LGBTQ (Lesbian, Gay, Bisexual, Transgender, Queer) trainings will also be analyzed and compared to the more traditional DIE trainings. This research will contribute to theory by evaluating different types of DIE trainings with regard to their effect on gender equality based on the three dimensions. From a practical perspective this research will allow practitioners to determine which type of training will most benefit their aims in increasing gender equality within their organization.

10.

• Umsækjandi / Applicant: Hans Peter Reiser
• Deild / Department: Tölvunarfræðideild/Department of Computer Science
• Doktorsnemi / Doctoral Student: NN
• Leiðbeinandi / Supervisor: Hans Peter Reiser
• Heiti verkefnis / Project title: Næsta kynslóð sveigjanlegra virkra og óvirkra aðferða til innskoðunar sýndarvéla/VMIflex – Next Generation Flexible Active and Passive Virtual Machine Introspection

Short description of the project:  
IT systems are more than ever faced with malicious attacks, and the need for advanced technology for the detection and in-depth analysis of highly sophisticated attacks is evident. VMIflex intends to advance the state of the art of virtual machine introspection (VMI) as a core technology for a broad range of IT security tasks, including intrusion detection, malware analysis, live forensics, and intrusion prevention. Current VMI systems are faced with a number of problems: (1) They depend on a specific hypervisor and VMI API and VMI applications are tedious to port to new environment; (2) They induce significant performance degradation on the target system, which reduces the practical applicability. (3) They support only heavy-weight hardware virtualization, but it is not possible to apply VMI security applications to light-weight container virtualization. VMIflex will significantly enhance VMI systems and tackle these three problems by (1) a systematic taxonomy of VMI features in current implementations and a mapping of VMI application requirements to these features, (2) a domain specific language (DSL) for expressing VMI functionality and a transformation approach for translating the DSL into target-specific optimization of VMI tools, (3) an extension of this transformation for container virtualization, and (4) a hybrid introspection approach based on code injection that minimizes context switches and thus enhances performance.

11.

• Umsækjandi / Applicant: Aðalsteinn Pálsson
• Deild / Department: Tölvunarfræðideild/Department of Computer Science
• Doktorsnemi / Doctoral Student: Aðalsteinn Pálsson
• Leiðbeinandi / Supervisor: Yngvi Björnsson
• Heiti verkefnis / Project title: Útskýringar á Ákvörðunum Gervigreindra Agenta/Explaining the Actions of Intelligent Game-Playing Agents

Short description of the project:
Artificial intelligence (AI) based systems are increasingly affected by our daily lives. Such intelligent computer agents are getting increasingly complex, for example, employing learned machine-learning models and extensive lookahead search, often exploring millions of possibilities. Unfortunately, as the complexity of those systems grows, it becomes more difficult to understand the rationality behind their decisions. This proposal proposes developing methods for explaining the decisions of intelligent (game-playing) agents' that employ deep neural-network models and heuristic search to make decisions, expanding on the current state-of-the-art of explainable AI (XAI) in two ways. First, by enhancing image-based XAI methods to apply to a broader set of problem domains and, second, by explaining the think-a-head reasoning process (the search). If successful, this work could have a widespread impact by allowing intelligent agents that use both models and search to better explain the rationality behind their decisions, thus building more valuable and trustworthy AI-based agents.

12.

• Umsækjandi / Applicant: Guolin Fang
• Deild / Department: Verkfræðideild/Department of Engineering
• Doktorsnemi / Doctoral Student: Guolin Fang
• Leiðbeinandi / Supervisor: Jón Guðnason
• Heiti verkefnis / Project title: Talgreinir og talgervill með einni lotu sem grunneining/Epoch dependent ASR and TTS models

Short description of the project:  
The field of speech signal processing, which includes text-to-speech and automatic speech recognition, has recently seen a dramatic increase in end-to-end machine learning approaches. These approaches perform the entire task of transforming speech into text and vice versa. This creates a problem when attempting to solve the next big challenge in language technology; prosody, and speaker identification. The end-to-end machine learning approaches ignore decades of speech feature research. We propose a new encoding layer that divides each speech segment into dynamically sized segments called epochs, instead of the traditional fixed 25 ms windows used in current literature. Using this encoding layer, the feature of the speech signal will be preserved and would not be damaged during the feature extraction process, which allows us to do more feature extraction in the following layers. In addition, we will apply our novel speech epoch layer in a supervised method of representing speech features in a machine learning context.

Continious grants 2023

Umsækjandi / Applicant	Heiti verkefnis / Project title	Deild / Department	Doktorsnemi / Doctoral student
Kristinn Torfason	Eiginleikar rafeindageisla frá rafeindalindum/Properties of Electron Beams from Microstructured Emitters	Verkfræðideild/Department of Engineering	Yuan Zhou
Snæfríður Guðmunds-dóttir Aspelund	Hugræn virkni fyrir skurðaðgerð við brjóstakrabbameini og áhrif ljósameðferðar á hugræna virkni eftir skurðaðgerð/Cognitive Impairment Prior to Breast Cancer Surgery and the Impact of Bright Light Therapy on Cognitive Function Following Surgery	Sálfræðideild/Department of Psychology	Snæfríður Guðmundsdóttir Aspelund
Rachel Elizabeth Brophy	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	Verkfræðideild/Department of Engineering	Rachel Elizabeth Brophy
Sævar Már Gústavsson	Hugrænn skilningur á háskahugsun og öryggisleitandi hegðun í almennri kvíðaröskun/Cognitive analysis of threat beliefs and safety-seeking behaviours in generalised anxiety disorder	Sálfræðideild/Department of Psychology	Sævar Már Gústafsson
Arash Sheikhlar	Flutningur á orsakasamþekkingum í gegnum rökleysu sem ekki er axiomatic/Causal Knowledge Transfer via Non-Axiomatic Reasoning	Tölvunarfræðideild/Department of Computer Science	Arash Sheikhlar
Illugi Torfason Hjaltalín	Gervigreind á 21. öldinni: þróun, hagnýting og innleiðing gervigreindar í opinbera geiranum á Íslandi/Artificial Intelligence in the 21st Century: Developing, Implementing and Deploying AI in Iceland’s Public Sector	Viðskiptadeild/Department of Business Administration	Illugi Torfason Hjaltalín
Björn Jón Bragason	Embætti þjóðhöfðingja Íslands. Frá stofnun konungsríkisins Íslands til vorra daga/The Office of the Head of State in Iceland from the founding of The Kingdom of Iceland in 1918 until present days	Lagadeild/Department of Law	Björn Jón Bragason

Ferðastyrkir 2023 / Ph.D. Student Travel Grant 2023

Umsækjandi / Applicant	Heiti verkefnis / Project title	Deild / Department	Doktorsnemi / Doctoral student
Camilla Carpinelli	Gagnafræði og vélanám fyrir sjálfbærni: Greining, spá og mæling á sjálfbærri innkaupahegðun og matarneyslu/Data Science and Machine Learning for Sustainability: Analysing, Predicting and Measuring Sustainable Purchasing Behaviour and Food Consumption	Tölvunarfræðideild/Department of Computer Science	Camilla Carpinelli
Ioana Duta-Visescu	Óljós vandamál og skipulagðir nemendur: Aukin hæfni miðuð að notendum/Wicked Problems and Structured Students: Extending User Centred Design Skills	Tölvunarfræðideild/Department of Computer Science	Ioana Duta-Visescu
María Sigríður Guðjónsdóttir	Sustainable utilization and optimization of the operation of geothermal power plants using reservoir stock modelling	Verkfræðideild/Department of Engineering	Arkaitz Manterola Donoso

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.

About the Fund

Two types of grants are available in 2023, a Ph.D. Student Grant and a Ph.D. Student Travel Grant. The Ph.D. Student Grant is similar in size to the Doctoral Student Grant of the Icelandic Research Fund (IRF). The grant covers the students' salaries (510.000 ISK per month, incl. salary-related costs) as well as travel costs for up to 300.000 ISK per grant year.

The Ph.D. Student Travel Grant is equal in size to a travel grant of the IRF in Doctoral Student Grants, i.e., 300.000 ISK per grant year.

Here you can find information about Rules on Reykjavik University Research Fund .