RESEARCH PROJECTS

RESEARCH PROJECTS

PERSEUS will recruit 40 doctoral candidates in total. Here you can meet the current PERSEUS PhD candidates


Bid Data and AI

Big Data and AI

Artificial intelligence (AI) is at the center of the digital transformation of society. Value gains from this technology are already happening, and such gains are expected to dramatically increase in almost every domain through improved productivity, quality, and personalization of offerings. Data acts as the fuel for AI, while AI is needed to extract actionable information from huge data sets. Big data and AI are hence synergistically coupled to each other. The 10 PhD positions in this area will focus on challenges in the areas of energy informatics, healthcare, manufacturing (industry 4.0), mobility and the maritime sectors. They will be set up with strong multi-disciplinary collaboration opportunities linked to relevant NTNU led research centers. The planned ESRs research will aim to go beyond limited focus responses, e.g. by addressing the more complex integration of AI into hybrid solutions (e.g., by combining explicit models and ML tools, classical control theory and AI solutions); to enhance systems with self-adapting, online algorithms that work natively from imbalanced data; and to enable learning from complex data and producing complex outputs. 


The Area of Big Data Analytics and AI

The Area of Big Data Analytics and AI

PhD candidate: Felix Ernst Friedrich Tempel
Supervisor: Heri Ramampiaro
Co-supervisor: Espen Alexander F. Ihlen

Felix will work in an R&D and innovation project named DeepInMotion funded by the Norwegian Research Council. The main objective of the project is to develop an explainable AI system and clinical service implementation to discover movement biomarkers for early detection of CP in infants. Felix will develop explainable AI techniques and methods that will contribute in generating new knSupervisorowledge and innovations, which will enable and provide decision support for early detection of motor disabilities in children. He will work in an interdisciplinary research group with researchers from Department of Neuromedicine and Movement Science, Department of Computer Science and clinics at St Olavs and Ålesund hosptitals.

 


Big Data and AI

Big Data and AI

PhD candidate: Kimji Pellano
Supervisor: Espen Alexander F. Ihlen
Co-supervisor: Heri Ramampiaro

Kimji will work in R&D and innovation project named DeepInMotion founded by the Norwegian Research Council. The main objective of the project is to develop an explainable AI system and clinical service implementation to discover movement biomarkers for early detection of CP in infants. Kimji will contribute in the generation of new knowledge and techniques in the research area of explainable AI for early detection of motor disabilities in children for clinical decision support. He will be first author of at least 3 articles in international peer-review journals or proceedings and attain international conferences within the field of AI and biomedical engineering.

 


Digital Twin

Digital Twin

A Digital Twin (DT) can be seen as a copy or models of a physical asset (from a single thermometer to a whole country, or even a human being), often connected through sensors and data. DT technology is envisioned to play a key role in the digital transformation of the society and many industry sectors. It can be an integrated part of other key technologies like IoT (data / state), AI (analytics / decision support), XR (visualization / dashboards) and Security (access / protect). DTs can be both static or more dynamic / real-time, and everything in between. A DT can be data-driven, physical/mathematical-driven or hybrid-driven. Its applications can range from planning, design, simulation, optimization and construction / manufacturing to monitoring, diagnostics, prevention/prediction, decision support, automation, maintenance, destruction/recycling and documentation. DTs can exist much longer than their physical counterparts (life-cycle property: from long before cradle to long after grave) and DTs can scale from a single device to complex systems (hierarchical property: e.g. sensor, room, floor, building, city, country). The industry is increasingly using DTs in their continuous strive to transform their business and many of the largest companies in Norway are among the key users of this technology. 

Digital Twins and Artificial Intelligence for Improved Personal Health and a more Sustainable Health Care System

Digital Twins and Artificial Intelligence for Improved Personal Health and a more Sustainable Health Care System

PhD candidate: Hamza Haruna Muhammed 
Supervisor: Frank Lindseth

We envision that a digital twin ecosystem (One Citizen - One Digital Twin) could substantially contribute to the effective realization of such a health care system. A Digital Twin (DT) is a digital/virtual representation/model of the physical twin/counterpart (PT), often connected through sensor data from the PT that enables the DT to provide feedback and predictions to the PT. DT technology is increasingly being used in domains like construction and manufacturing and is expected to play a key role in the digital transformation of many areas in the coming years. In the case of health-related digital twins (DTs) this means that your own personal twin would look after you throughout life, that this twin, that you are in charge of, will know as much as possible about you, and that the combined data from all the twins are used to generate new actionable knowledge applicable in various fields to both yourself (self-management of health) and the health care system in general (e.g. decision support) through the functionally provided by your twin (i.e. bridging the gap between citizens and the health-care system).

Hamza will contribute to the realization of a proof-of-concept DT ecosystem, focusing on wearables and state-of-the-art AI research connected to the analysis of vital signs and time series. He will also be given a unique opportunity to form how a future data-driven health care system might look like. The project is part of ongoing activity and related projects for health and medicine (e.g. wearables, distance follow-up, home hospital) among key NTNU faculties and departments with associated partners and collaborators.

 


Digital Twin

Digital Twin

PhD candidate: Daniel Menges  
Supervisor: Adil Rashid

Digital twinning is now an important and emerging trend in autonomous transport. Also referred to as a computational megamodel, device shadow, mirrored system, avatar or a synchronized virtual prototype, it is bound to play a transformative role not only in how we design and operate cyber physical intelligent systems, but also in how we advance the modularity of multi-disciplinary systems to tackle fundamental barriers not addressed by the current, evolutionary modeling practices. At the heart of digital twins are real-time, accurate, generalizable, trustworthy and self-evolving models and hence the focus of the research is placed here. More specifically the research topic within the context will be to create better situational awareness for autonomous ships by instilling physical realism into their digital twins through: Developing tools and algorithms for better description and perception of the internal condition of the ship´s performance, condition of the various components of the ship etc.

Developing tools and algorithms for better description and perception of the external environmental environment of the ship: eg-. Weather condition, state of the ocean

Better comprehension of the immediate surrounding like how the other vessels, boats are communicating and maneuvering around.

Predicting the situation on a short and long term horizon for better reactive and planned navigation


Digital Twins for Autonomous Vessels

Digital Twins for Autonomous Vessels

PhD candidate: Luka Grgičević
Supervisor: Ottar Osen

This position is a part of Cyber-Physical Systems Laboratory (CPS Lab) and NTNU SFI AutoShip. This PhD project is a part of the PERSEUS doctoral programme: A collaboration between NTNU- Norway’s largest university, 11 top-level academic partners in 8 European countries, and 8 industrial partners within sectors of high societal relevance.

 

 

 


Internet of Things

Internet of Things

This thematic area aims at advancing knowledge and understanding of IoT technology, which is a key enabler for the digital transformation of the society and is used in a large variety of domains (moving out of traditional ICT and ranging from e-health to Industry 4.0). IoT technology embraces heterogeneous networks of devices with various combinations of interaction in terms of sensing, communication, computation, and control, thus a multi-disciplinary approach is essential in order to exploit and manage its full potential. There will be 7 linked PhD positions announced focusing mostly on Energy, Mobility, and Ocean, with a common theoretical framework relying on effective processing of raw sensor data.  


Designing an Experimental Platform for Internet of Things Research

Designing an Experimental Platform for Internet of Things Research

PhD candidate: Lukas Liedtke
Supervisor: Magnus Jahre

Experimental Platform for Intermittent IoT Research (EPIoT) which will enable research on intermittent IoT applications by designing the platform around the energy and sensor subsystems. More specifically, EPIoT will combine a range of energy harvesters (see [8]) with configurable energy storage (e.g., super-capacitor banks) and slow (e.g., temperature and humidity) and fast sensors (e.g., vibration and sound). EPIoT’s compute and communication System on Chip (SoC) will inspect the energy storage to dynamically selecting operation points in energy-equilibrium. Once operational, EPIoT can serve as an enabler of further research. For instance, multi-node systems can be straightforwardly implemented as EPIoT nodes are scalable by design (i.e., they are self-powered and communicate wirelessly). As aforementioned, intermittent computing systems are critical to deliver the scalability required by foreseen IoT applications, and EPIoT will enable better understanding the fundamental energy versus performance trade-offs facing such applications. Moreover, EPIoT will be directly applicable to emerging applications such as predictive maintenance (highly relevant to the manufacturing and energy domains) as well as (remote) health monitoring. Moreover, removing batteries from ULP-nodes will contribute to making IoT applications more sustainable (by reducing waste).

 


Industry 4.0 Digital Twin for Offshore Wind Farms

Industry 4.0 Digital Twin for Offshore Wind Farms

PhD candidate: Evi Elisa Ambarita
Supervisor: Agus Hasan
Co-supervisor: Francesco Scibilia

The idea of this project is to leverage the use of AAS for digital twin development of offshore wind farm. Evi will investigate current applications of AAS in other industries that could be relevant for wind farms, possibility to transfer AAS learning and solutions from other industries. In general, this task should look at the opportunities of using the AAS framework in the offshore wind industry and highlight possible challenges for implementation, which include architecture design, data requirements, predictive analytics, information modeling, and simulation and visualization solutions for asset management and predictive maintenance. Furthermore, Evi will implement prototypes of simulation and visualization solutions based on Digital twin (AAS-based). Use cases will be provided from the Hywind Tampen wind farm operated by Equinor.

 


Information and Cyber Security

Information and Cyber Security

The increasing digitalization of society comes along with more vulnerabilities of and increased dependency on digital infrastructure and systems. Successful digital transformation cannot be achieved without ensuring that digital services will function as expected, anywhere, and at all times, whilst preserving the security of information and the privacy of individuals. Information security refers to the protection of digital systems and infrastructure, the data on them, and the services they provide, from intentional or accidental harm. Information security is an interdisciplinary area that combines information and communication technologies, management, law, economics, mathematics, and psychology. It is envisaged to announce 8 PhD positions and it is expected that the PhD students that will be recruited will acquire knowledge and will develop skills that will facilitate the secure digital transformation and will contribute to creation of significant positive impact including through reduced negative impact (due to reduced exposure to cyber risks) that ultimately leads to sustainable value creation.  


Digital Economics and Sustainability

Digital Economics and Sustainability

PhD candidate: Gabriel Andy Szalkowski
Supervisor: Harald Øverby

Digital markets are dominated by a few global digital conglomerates, including Apple, Amazon, Facebook, and Google. These companies have huge impact on the innovation, production, and trade of digital services. There is a concern that these markets are not performing optimally, witnessed by recent legal actions from both the EU and the US Competition Authorities (see e.g., US v. Google (2020), US v. Facebook (2020), and EU v. Apple (2021)). A deeper understanding of these digital markets and their business models is needed to (i) restore competition, (ii) promote innovation, and (iii) ensure sustainability according to SDG 9.

The main research goal for Gabriel is to (i) analyze current digital markets and business models using system dynamic modelling and to (ii) develop and test new policies and business models promoting competition and innovation in the context of sustainability in future digital markets. His PhD position is highly cross-disciplinary, combining knowledge from technology, economics, business, and law.

 


Extended Reality

Extended Reality

Extended Reality gathers together the fields of Virtual Reality, Augmented Reality and Mixed Reality in a holistic way aiming at providing interactive digital content immersing the user completely and providing the best possibly Quality of Experience to the user. Extended Reality is by nature transdisciplinary and requires both soft and hard skills in the intersection between art and technology.  


EU project

EU project

EU logo This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 101034240.