Euromicro Conference on
Software Engineering and Advanced Applications

August 26 – 28, 2020
Virtual Event
Organized from Kranj | Slovenia

SEAA 2020

SEAA 2020 Call For Papers Committees Submissions Registration

Abstract Submission Deadline:

16 March 2020 (AoE)

Paper Submission Deadline:

13 April 2020 (AoE) (Extended)

Notification of Acceptance:

18 May 2020 (AoE)

Camera-Ready Papers:

21 June 2020 (AoE)

Call for Papers

Special Session @ 46th EUROMICRO SEAA Conference in Portorož / Slovenia

Data and AI driven engineering

August 26-28, 2020

Important Dates:

  • Abstract submission to tracks and sessions: March 16, 2020 (AoE)
  • Paper submission to tracks and sessions: April 13, 2020 (AoE) (Extended)
  • Notification of accepted papers: May 18, 2020 (AoE)
  • Camera-ready paper due: June 21, 2020 (AoE)

Motivation: Over the last decade, the prominence of artificial intelligence (AI) and specifically machine- and deep-learning (ML/DL) solutions has grown exponentially. Because of the big data era, and with companies collecting customer and product data from an increasing number of connected devices, more data is available than ever and can be used for training ML/DL solutions. In parallel, the progress in high-performance parallel hardware such as GPUs and FPGAs allows for training solutions of scales unfathomable even a decade ago. These two concurrent technology developments are at the heart of the rapid adoption of ML/DL solutions in industry.

The hype around AI has resulted in virtually every company has some form of AI initiative, or host of AI initiatives, ongoing and the number of experiments and prototypes in industry is phenomenal. However, research shows that the transition from prototype to industry-strength, production-quality deployment of ML/DL models proves to be challenging for many companies. The engineering challenges, and the related data management challenges, prove to be significant even if many data scientists and companies fail to recognize these.

In this special session, we invite articles on the following topics (though not limited to):


  • Solutions to assess and guarantee data quality for ML
  • Design methods and approached for ML/DL models
  • Distributed ML/DL models in embedded systems
  • Automated labelling of data for ML
  • Adoption of DataOps practices in large-scale software engineering
  • Engineering aspects of training, transfer learning and reinforcement learning
  • Engineering effective ML/DL deployments
  • Management of data pipelines for ML/DL
  • Automated experimentation
  • Experimentation and data driven development practices

The conference proceedings in the last years have been published by the IEEE Computer Society. The format is the IEEE two-column proceedings format (8 pages for full papers and 4 pages for short papers).

Submission Guidelines: SEAA 2020 encourages the submission of full research papers (maximum 8 pages), short papers and tool demo papers (maximum 4 pages), and posters. Papers follow a single-blinded reviewing process and must contain original unpublished work, describe significant novel contributions, and provide evidence on the validation of results. In particular, reports on industrial applications are welcome.

Submissions URL: (choose Data and AI driven engineering track when submitting)

Conference Publishing Services (CPS) will publish accepted papers in the conference proceedings and the proceedings will be submitted to the IEEE Xplore Digital library and indexing services.

Please note that it is planned to select best papers among all tracks of SEAA and present them with an award. A selection of best papers will be invited to submit extended versions for tentative publication in a requested Special Issue of a Journal (under negotiation).

Special Session Organizers:
Helena Holmström Olsson,, Malmö University, Sweden
Jan Bosch,, Chalmers University of Technology, Sweden

Program Committee:
Aleksander Fabijan, Microsoft, Seattle, USA
Pavel Dimitriev, Outreach, Seattle, USA
Christoph Elsner, Siemens AG, Corporate Technology, Germany
Matthias Tichy, Ulm University, Germany
Eric Knauss, Chalmers University of Technology
Michael Felderer, University of Innsbruck, Austria
Daniel Ståhl, Linköping University, Sweden
Christa Schwanninger, Siemens AG, Corporate Technology, Germany
Ilias Gerostathopoulos, Technische Universität München
Stefan Wagner, University of Stuttgart, Germany