SweDS is a national event with a focus of maintaining and developing Swedish data science research and its applications by fostering the exchange of ideas and promoting collaboration within and across disciplines. This yearly workshop brings together researchers and practitioners of data science working in a variety of academic, commercial, industrial, or other sectors. Past workshops has included presentations from a variety of domains, e.g., computer science, linguistics, economics, archaeology, environmental science, education, journalism, medicine, health-care, biology, sociology, psychology, history, physics, chemistry, geography, forestry, design, and music. SweDS20 is organized by the Luleå University of Technology (LTU).
Call for Contributions
We invite academic and industrial researchers and practitioners to share their work by giving a talk, or presenting a poster. Contributions should be submitted through Easychair in two different categories
1) Extended abstracts: contributions for the non-archival abstract track can be from 300 words, to a page. Acceptable submissions for this track include description of work-in-progress works, previously published works, and works under review too.
2) Full papers: of maximum 6 pages of content (plus up to 2 pages of references) to be included in the planned proceedings. Submissions for this track are required to be novel, previously unpublished works that are not under review for other conferences or publications during the SweDS review cycle. For more detailed requirements for full paper submissions, please read below.
Submissions are collected via Easychair
The requirements for full paper submissions in more detail can be found HERE
- Submission deadline: 2̶0̶2̶0̶ ̶A̶u̶g̶u̶s̶t̶ ̶3̶1̶ 2020 September 15
- Notification of acceptance/rejection: 2̶0̶2̶0̶ ̶S̶e̶p̶t̶e̶m̶b̶e̶r̶ ̶1̶5̶ 2020 October 1
- Workshop: 2020 October 29-30
As per the government guidelines, there is a limitation on public gatherings. Because of this, the number of registrations for in-person participation is limited, so we encourage those who want to attend in person to register as soon as possible (limitations do not apply to online attendance). For more information regarding COVID19 situtation and travel, please visit Public Health Agency and Ministry of Foreign Affairs.
Detailed program is available HERE.
- Prof. Marcus Liwicki (EISLAB Machine Learning, LTU)
- Dr. György Kovács (EISLAB Machine Learning, LTU)
- Michael Nilsson (Centre for Distance-spanning Technology)
- Dr. Pär-Erik Martinsson (ProcessIT Innovations)
- Gustav Grund Pihlgren (EISLAB Machine Learning, LTU)
- Dr. Madhav Mishra (Division of Operation, Maintenance and Acoustics, LTU)
- Dr. Rajkumar Saini (EISLAB Machine Learning, LTU)