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Data-centered and Secure Computing (DSComputing)

Focusing on data, we will obtain value and impact by computing while maintaining privacy and trustworthiness.

Publisert: Endret:
About us
Researchers

10

PhDs

8

Projects

10

Using Big Data in the Triangulum smart city project

The group focuses on real-world solutions using computing technologies (cloud/edge, AI, blockchain, high performance, etc) in domains such as smart cities, health and energy, while managing the cloud data hub infrastructure at two sites: UiS campus and Green Mountain. The group ensures security and privacy remain paramount for the trustworthiness of any services and data management. DSComputing is part of the university's initiative on artificial intelligence – Stavanger AI Lab.

project:

Partnership for joint Curriculum Development and Research in Energy Informatics (PACE)

PACE is a project under the Norwegian Research Council's INTPART programme.

The transition to a globally sustainable low-carbon emission society requires a significant increase in the use of renewable energy. We are facing increased decentralized energy production, and digitalization of the whole value chain.

Advanced use of ICT is crucial for realizing this energy shift. This is confirmed in the revised national strategy for Norway on energy research, Energy21 which recommends to give Digitalization and integrated energy systems top priority. In this context, the energy sector is facing two key challenges:

  1. The sector must be able to apply state-of-the-art ICT
  2. There is a lack of talents with the necessary expertise in the intersection between energy systems and ICT, which we refer to as energy informatics.

This project, which is a collaboration between research groups at University of Stavanger, University of Oslo, Technical University of Munich, and University of Lille, is one response to these challenges. The groups form the core of energy informatics educators and researchers at their respective institutions.

Energy informatics (EI) is an emerging interdisciplinary field that deals with the digitalization of the whole value chain of the energy sector. EI is concerned with how to exploit state-of-the-art ICT methods, tools and techniques to achieve sustainable energy generation and use. Research and education in EI requires a solid foundation in informatics. EI research and education can therefore naturally be envisioned as extensions of research and educational programs in informatics.

The goal of the project is to strengthen the research and educational activity on EI at the partner institutions.

Summer school for early-stage PhD students and MSc students. Time and place: Aug. 29, 2022 – Sep. 2, 2022, Sundvolden Hotel, Dronningveien 2, 3531 Krokkleiva, Norway. Hosted by University of Oslo.

The partners of the two projects LUCS and PACE, University of Oslo, Norway, Simula Metropolitan Center for Digital Engineering, Norway, University of Stavanger, Norway, University of Lille, France, Technical University of Berlin, Germany, GT-ARC, Germany, and Technical University of Munich, Germany, are jointly organizing the Summer School From Energy Systems to Energy Justice.

The target audience for the summer school is early-stage PhD students and MSc students in the related degree programs. Students from the host universities and institutes are particularly encouraged to apply.

Location: Sundvolden Hotel, Dronningveien 2, 3531 Krokkleiva, which is close to the city of Oslo, Norway. Hosted by University of Oslo.

Dates: August 29 – September 2, 2022.

The transition to a globally sustainable low-carbon emission society requires a significant increase in the use of renewable energy, improving energy efficiency, and reducing energy consumption. We are facing increased decentralized energy production, and digitalization of the whole value chain. We must learn to exploit state-of-the-art ICT methods, tools and techniques to achieve sustainable energy generation and use. However, the technical aspect is just one part of this equation, where the social aspect is just as important. There is a need to integrate technological and social science research to develop solutions that adopt the perspectives of social inclusion and energy justice in developing new solutions. That is, inclusion of all groups in society and policy approaches to support fair distribution of energy generated on-site, costs and benefits, the recognition of all involved groups, and fair representation in decision making.  New knowledge is increasingly at the intersection of Energy technology, Energy Informatics, Communication systems, Social Sciences Psychology, and Data and Energy Law.

This year's summer school focuses on these areas of intersection and tools that facilitate research at these intersections. Energy sharing and decentralized markets require mechanisms to securely and privately facilitate the interactions in fair and equitable ways. Battery management and storage systems help enable stable connectivity. Simulation and emulation tools help us to examine how these interactions will play out in future systems. Stochastic optimization is a powerful tool to help us to find the best approaches to the interactions despite the uncertainty. Adopting this approach will enable us to address the cross disciplinary aspects necessary to develop a holistic and autonomous framework for transactive energy management.

The summer school will cover contemporary topics in energy systems along with the interaction to socio-technical perspectives. These include:

  • Energy sharing: Local Markets and Community Energy Storage
  • Battery Management Systems and Industry Scale Storage Solutions
  • Energy system simulation and emulation
  • Microgrids and Virtual power plants
  • Energy justice: Social, psychological, and regulatory aspects of the energy transition
  • Security and Privacy of Energy Systems and Local Energy Markets
  • Decentralized Markets Design and Models for Sustainable Energy Systems

The lectures will cover the recent trends and modern approaches in the above topics. Lectures in each field will be presented from various perspectives, encompassing technical and social aspects from both academics and industry. In addition, the summer school will include hands-on work in the form of a stochastic optimization tutorial. Finally, 1-minute madness presentations from students to introduce their current research will align interests and lead to future collaborations.

Applying for the Summer School

Please apply here. Included in the application, you will be asked to upload a CV, letter of support from your supervisor, transcripts and a motivation statement. Deadline for applications is 19 June, 2022. Accepted students will be notified by the beginning of July.

Travel and Accommodation

Accommodation in double rooms will be provided to the admitted students for the entire duration of the summer school. Arrival at the hotel will be Sunday, the 28th of August with checkout by noon on the 2nd of September. All meals from the evening of the 28th until lunch on the 2nd are included. Upon presentation of documentation, travel expenses will be reimbursed after the summer school with a maximum of €500 for travels within Europe. For travel from outside of Europe, expenses will be reimbursed up to a maximum of €1200. Please note, only economy class travel will be reimbursed. Reimbursable travel expenses include airplane tickets, train or bus.

Currently there are no restrictions in Norway due to Covid-19. As we get closer to the event, updated travel information will be made available.

Contact Information

Russel Wolff, Email: russel.wolff@uis.no; Tel.: (+47)47903118

David Hayes, Email: davidh@simula.no; Tel.: (+47)99870774

project:

Smart Community Neighborhood – driven by energy informatics (NFR EnergiX)

Solcellepanel

This project focuses on the development of mechanisms which will allow prosumers to share information about their production and consumption behavior.

It creates a decentralized virtual neighborhood where each household operates autonomously and trades energy with other households and communities, in which case, the central authority or the main grid only act as a facilitator. Such mechanisms will be particularly applicable for fluctuating loads and solving congestion problems.

The project aims to achieve this with ICT based smart-solutions. Machine learning based methods are used to learn and predict household production and consumption behavior. Incentive systems for energy trading are facilitated through the use of blockchains.

Furthermore, edge and fog computing drive energy information solutions. Finally, all technical components are driven by data privacy and security elements.

PROJECT:

Kenya-Norway Mobility Programme for Computer Science Education

Sju hender møtes

KeNoMo is a SIU/NFR NORPART project.

The objective of the project is to facilitate mutual student mobility and academic cooperation between the partners, and will thus enhance the quality of computer science education in both Norway and Kenya.

PROJECT:

Cloud Artificial Intelligence for Pathology (CLARIFY)

Logo for the Clarify project

An EU ITN project, CLARIFY’s main goal is to develop a robust automated digital diagnostic environment based on artificial intelligence and cloud-oriented data algorithms that facilitates whole-slide-image (WSI) interpretation and diagnosis everywhere with the aim of maximising the benefits of digital pathology and aiding pathologists in their daily work.

Read more about the project on the BMDLab page.

PROJECT:

Future Energy Hub (NFR)

To forskere rygg i rygg med ulike energibærere i bakgrunnen, med grønt raster over

Future Energy Hub aims to create greener buildings and districts in collaboration with business and the public sector. The project serves as a connection point for various disciplines. By connecting cutting-edge expertise from several fields, the best possible basis is created for innovative innovation and development towards greener cities.

Read more on Future Energy Hub's page (in Norwegian)

PROJECT:

Digital Well Center (DigiWells)

Full name: Digital Well Center for Value Creation, Competitiveness and Minimum Environmental Footprint.

Illustrasjon av bore- og brønnteknologi

The objective of this NFR/SFI centre is to develop new knowledge, methodologies, and innovative solutions to improve the well delivery process enabled by digitalization, new sensors, high speed telemetry, automation, and autonomy.

Link to more information at NORCE (in Norwegian)

PROJECT:

Distributed fibre optic sensing for production optimization (DIFI-PRO)

This NFR project will perform experiments and modelling to increase our understanding of distributed fibre optic measurement systems as a cost-efficient tool for production optimization and increased field recovery.

More information on the NORCE website

PROJECT:

5G Management and Orchestration for Data and Network Integration

5G-MODaNeI focuses on allocating together the network resources of 5G and the data resources of Multi-access Edge Computing (MEC).

5G-MODaNeI logo

The risks and the vulnerabilities for attacks and failures in 5G MEC will be identified. The impact of joint data and network resource allocation on security and dependability in 5G MEC will be determined. Next, innovative and intelligent solutions will be created. These solutions will allocate the network and data resources to maximize the security and dependability in 5G MEC.

More info on the 5G-MODaNeI page

PROJECT:

Next Generation 3D Machine Vision with Embedded Visual Computing

The overall objective of this research is to give up the currently manual and time-consuming operational processes with well-composed digitalization using real-time 3D vision and learning processes.

This research aims to initiate an automated process deploying high-precision 3D sensing and online visual learning engines that operate in natural environments and are able to adapt in a holistic lifetime manner to changes during operations.

It targets establishing a groundbreaking technological concept for 3D machine vision as an interdisciplinary initiative linking cost effective and reliable depth sensing with advanced computer vision and embedded artificial intelligence to tackle challenges posed by time-varying visual scene perception in natural environments.

This research has a potential to a radical change in many parts of the value chain in the industry and society and selected scenarios will be designed for impact evaluation and opening up integration opportunities.

UiS will lead one of the work packages in the 3DSmartCam project: What are the capabilities and performance of the new 3D machine vision for digitalization of services and processes?

PROJECT:

Automated Well Monitoring and Control

Well surveillance and control remain key issues for industries like oil and gas (O&G), geothermal, geological carbon storage (CCS) and compressed air energy storage (CAES).

Significant progress with real-time well measurements and automated data gathering has recently been achieved, while interpretation and well control optimization remain labour and time-consuming work mainly done manually.

The project aims at development and testing of a new methodology and tool (prototype software) for automated injection well monitoring and control based on real-time pressure, temperature and rate data. The basis is timelapse Pressure Transient Analysis (PTA) providing capabilities to monitor well performance and interference, containment of injected fluids and safety of abandoned wells.

Advanced interpretation and automation will be achieved via combining model- and data-driven approaches. Real field data will guide the project tasks and priorities and serve as a testing and application environment for the research and development. Automated well monitoring and warning system will be integrated with injection well control. The control includes rate changes designed to send signals with real-time interpretation of the response (on-the-fly well testing) to optimize well performance and interwell communication and prevent injection safety issues. The automated solution developed in the project will reduce costs, improve efficiency and minimize environmental footprint in O&G and facilitate CCS, CAES and geothermal industries.

UiS will lead one of the work packages in the Autowell project on prototype tool development.

Our researchers

Professor
51832013
Faculty of Science and Technology

Department of Electrical Engineering and Computer Science
professor
51832061
Faculty of Science and Technology

Department of Electrical Engineering and Computer Science
Førsteamanuensis
51832832
Faculty of Science and Technology

Department of Electrical Engineering and Computer Science
Professor
51831051
Faculty of Science and Technology

Department of Electrical Engineering and Computer Science
Professor II
Trondheim
Faculty of Science and Technology

Department of Electrical Engineering and Computer Science
Førsteamanuensis II
Faculty of Science and Technology

Department of Electrical Engineering and Computer Science
ekstern u/lønn
Faculty of Science and Technology

Department of Energy Resources
Professor
51831560
EOJ-218
UiS Business School

Department of Innovation, Management and Marketing

Our PhD students

Ekstern u/lønn
51832839
Faculty of Science and Technology

Department of Electrical Engineering and Computer Science
Forsker
Faculty of Science and Technology

Department of Electrical Engineering and Computer Science
Stipendiat
Faculty of Science and Technology

Department of Electrical Engineering and Computer Science
Ekstern u/lønn
Faculty of Science and Technology

Department of Electrical Engineering and Computer Science
Stipendiat
Faculty of Science and Technology

Department of Electrical Engineering and Computer Science
Stipendiat
Faculty of Science and Technology

Department of Electrical Engineering and Computer Science

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