Linnaeus University Centre for Data Intensive Sciences and Applications
The DISA research centre at Linnaeus University focuses its efforts on open questions in collection, analysis and utilization of large data sets. With its core in computer science, it takes a multidisciplinary approach and collaborates with researchers from all faculties at the university.
Our research
In today's society, sensors, computers, communication platforms and storage technologies give us access to previously unmanageable volumes of data, so-called Big Data. The conversion of data into actionable knowledge creates new opportunities and significant economic values. Big Data has revolutionised both the commercial world and research in many areas, and has opened up for new interdisciplinary collaborations.
The Linnaeus University Centre (Lnuc) for Data Intensive Sciences and Applications (DISA) addresses data-driven methods to gain deeper knowledge and understanding in a variety of applications in engineering, science and humanities. Research in computer science, media technology, signal processing and statistics represents the technical core of the center. Combined with research from application fields, such as astrophysics, engineering, linguistics, social science and e-health, we create a unique dynamics.
Exploiting data to gain manageable information and useful knowledge is not a research venture alone. There is also a large collaboration interest in the industry and the public sector. DISA works closely with several clusters, networks and individual companies representing the IT and heavy vehicle industries, the health sector and municipalities and agencies. These partnerships combine excellent research with practical solutions to specific challenges in society, for the mutual benefit of researchers from different scientific disciplines and of external partners.
Seed projects
At DISA, we encourage and support seed projects. Seed projects are intended to promote and nurture excellence research, development, and innovation in data intensive sciences and applications with cross-discipline collaboration. The seed project should belong to one of the research areas within DISA. Please define which core DISA research area/group the seed project belongs to in the proposal, and make sure that the research coordinator of the area is aware of the proposal.
Financial support
DISA can finance up to SEK 100 000 to initiate research cooperation with a connection to data intensive sciences and applications. External partners can, if required, be funded up to a maximum level of 50 % of DISA’s project funding. They need to co-finance the project with the same amount.
During 2023, there is SEK 700 000 in total available to apply for seed funding.
Objectives for seed projects
The seed project should increase the chances of applications for external funding and/or of publications in top tier journals. Seed project proposals should argue that the planned activities are decisive for achieving the(se) objective(s). Activities may include, but are not limited to:
- Building new cross-disciplinary teams of researchers and/or with industry, aiming for a long-term collaboration.
- Exploring novel research questions in a pre-study.
- Collecting large amounts of data and running initial experiments and analyses.
- Implementing research demonstrators or infrastructure.
Prerequisites and evaluation criteria
The project consortium should consist of one or more researches from DISA. The researchers in the consortium should come from different research disciplines, in order to build a strong cross-discipline collaboration. It is important that all members in the consortium have an active role in the seed project. Please describe the different roles in the proposal. Industry/public sector collaboration is a plus. Please define clearly the added value that the seed project will give to the consortium.
If any member of the consortium is active in another ongoing seed project, please explain the relation between the projects/research.
The evaluation criteria include relevance of the proposal for the operational and strategic goals of DISA, feasibility of the project activity, and chances to eventually succeed with an application for external funding and/or of publications in top tier journals.
Read about the application process in this pdf file. Applications should be submitted no later than the last day in each month to be handled during the following DISA coordinator meeting.
For more information about the seed project concept, please contact Diana Unander.
Ongoing seed projects
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Seed project: Biosensor Testbed at the IoT Lab The objective of this project is to explore the potential applications of biosensors for the continuous monitoring and management of various health…
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Seed project: Development of an intelligent wearable – the DIWAH study The overall goal of the research in this seeding project within the Linnaeus University Center for Data Intensive Sciences and…
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Seed project: Investigate Machine Learning Techniques for Decision-Making Support in K-12 Educational Context The main aim of this seed application is to investigate the use and application of Machine…
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Seed project: Machine learning stabilized steady-state advective-diffusive heat transport This seed project aims to explore and use the strengths of Scientific Machine Learning (SciML) to solve the…
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Seed project: Using Natural Language Models for Extracting Drug-Related Problems (NLMED) The overall goal of the research in this seed project within the Linnaeus University Center for Data Intensive…
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Seed project:Automated Assembly/Disassembly Instructions (ADDITION) The project aims at building a consortium interested in laying the foundation for harnessing the power of AI and digitalization for…
Concluded seed projects
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Seed project: A platform to collect and analyze canoe/kayak training data The main objective for this seed project within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA)…
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Seed project: An Exploration of the Challenges and Possibilities of Multidimensional Visualization in the Context of Visual Learning Analytics The main objective for this seed project within Linnaeus…
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Seed project: Analyzing state-of-the-practice for self-adaptive systems in industry using data analytics The main objective for this seed project within Linnaeus University Centre for Data Intensive…
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Seed project: Data intensive analysis for identification and prediction of risk medications The main objective for this seed project within Linnaeus University Centre for Data Intensive Sciences and…
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Seed project: Data-intensive tools for effective carbon mitigation in forestry The main objective for this seed project within Linnaeus University Centre for Data Intensive Sciences and Applications…
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Seed project: Developing the Skeleton Avatar camera Technique (SAT) as a rapid, valid and sensitive measurement of mobility in elderly persons The main objective for this seed project within Linnaeus…
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Seed project: Digitized ancient remains detection The main objective for this seed project within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) is to explore if…
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Seed project: European spruce bark beetles; advanced predictive forecasting by means of machine learning The main objective for this seed project within Linnaeus University Centre for Data Intensive…
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Seed project: Exploring data and establishing routines for collaboration on energy experiments The main objective for this seed project within Linnaeus University Centre for Data Intensive Sciences…
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Seed project: IoT for ships – an untapped data resource The main objective for this seed project within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) is to establish…
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Seed project: ODXVR x NTS The main objective for this seed project within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) was to submit an external funding application.…
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Seed project: Smart-Troubleshooting in the Connected Society The main objective for this seed project within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) was to…
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Seed project: Towards a data-driven approach to ground-fault location The main objective for this seed project within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) is…
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Seed project: User performance data from a video-based application/platform The main objective for this seed project within Linnaeus University Centre for Data Intensive Sciences and Applications…
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Seed project: Using Artificial Intelligence to Detect Acanthamoeba Keratitis in the eye - the AIDAK study Applicants The overall objective of the research for this seed project within Linnaeus…
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Seed project: Vibration-based strength grading of sawn timber The main objective for this seed project within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) was to…
Research groups
The Linnaeus University Centre for Data Intensive Sciences and Applications embraces the following research groups.
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AdaptWise The AdaptWise research group conducts research on the foundations and engineering of self-adaptive software systems. The primary focus is on: i) dynamic architectures and runtime mechanisms…
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Computational Social Sciences The research in the area Computational Social Sciences within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) is about producing and…
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Data Intensive Digital Humanities The research area Data Intensive Digital Humanities within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) is a network that brings…
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Data Intensive Software Technologies and Applications (DISTA) The research group Data Intensive Software Technologies and Applications studies data-driven approaches, such as machine learning,…
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Deterministic and Stochastic Modelling The research field Deterministic and Stochastic Modelling within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) brings together…
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E-health – Improved Data to and from Patients The research in the e-health area within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) will result in novel ways for…
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Forestry, Wood and Building Technologies Within the research area Forestry, Wood and Building Technologies, the objective of Linnaeus University Centre for Data Intensive Sciences and Applications…
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High-Performance Computing Center (HPCC) The High-Performance Computing Center (HPCC) offers computational and storage resources to help researchers to solve big computing and big data problems.…
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Information and Software Visualization (ISOVIS) The research group Information and Software Visualization mainly focuses on the explorative analysis and visualization of large and complex information…
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Smart Industry Group Smart Industry Group (SIG) is an interdisciplinary research group featuring expertise from computer science and mechanical engineering. SIG's focus is making production and…
PhD studies
Within DISA, several doctoral students are connected to our research groups. The doctoral students either focus on the foundational technologies or have a more thematic aim.
There is also a graduate school for industrial doctoral students in computer science connected to DISA: Data Intensive Applications (DIA). DIA focuses on applied research, addressing the big data and artificial intelligence challenges of our industry partners. The industry graduate school is funded by the Knowledge Foundation, Linnaeus University and the participating companies.
Current
Short notices
Publications
Research leaders
Around thirty researchers from different disciplines at Linnaeus University constitute the critical mass within DISA. The scientists are divided into seven groups led by the following researchers.
- Andreas Kerren Professor
- +46 470-76 75 02
- andreaskerrenlnuse
- Deliang Dai Senior lecturer
- +46 470-70 88 53
- deliangdailnuse
- Diana Unander Research and Project Coordinator
- +46 470-76 78 65
- +46 73-057 70 64
- dianaunanderlnuse
- Giangiacomo Bravo Professor
- +46 470-70 87 82
- giangiacomobravolnuse
- Johan Fransson Professor
- +46 470-76 70 42
- +46 70-660 86 97
- johanfranssonlnuse
- Jukka Tyrkkö Professor
- +46 470-76 78 52
- jukkatyrkkolnuse
- Lars Håkansson professor, head of department
- +46 470-70 83 50
- +46 73-338 57 12
- larshakanssonlnuse
- Mikko Laitinen Professor
- mikkolaitinenlnuse
- Morgan Ericsson Associate professor, head of department
- +46 470-76 78 72
- +46 72-594 17 48
- morganericssonlnuse
- Tora Hammar ASSOCIATE PROFESSOR
- +46 480-49 71 76
- +46 72-594 97 16
- torahammarlnuse
- Welf Löwe Professor
- +46 470-70 84 95
- +46 76-760 36 62
- welflowelnuse
Doctoral students
Doctoral students
- Dag Björnberg
- dagbjornberglnuse
- Felix Viberg
- felixviberglnuse
- Gaurav Garg
- gauravgarglnuse
- Joel Cramsky
- joelcramskylnuse
- Kailash Chowdary Bodduluri
- kailashchowdaryboddulurilnuse
- Nemi Pelgrom
- nemipelgromlnuse
- Niels Gundermann
- nielsgundermannlnuse
- Nils Johansson
- nilsjohanssonlnuse
- Rakhshanda Jabeen
- rakhshandajabeenlnuse
- Senadin Alisic
- senadinalisiclnuse
- Tibo James Liam Bruneel
- tibojamesliambruneellnuse