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Abstract: Data intensive engineering is a one-year research-based project course in which we are having very talented international students. The course is organized within the framework of our Erasmus Mundus Joint Master’s Degree Programme on the Engineering of Data Intensive Software Systems (EDISS), https://www.master-ediss.eu. EDISS is a prestigious EU funded joint international MSc programme with three partners, University of the Balearic Islands, University of L’Aquila and Mälardalen University.
The objectives of this course are to give the students a real-life experience through a one-year hands-on project-based course. The course project is defined together either with academic and/or industrial partners. The tasks of the projects are carefully defined in small blocks conforming to each theoretical objective of our four courses on Data Science, Artificial Intelligence, Machine Learning and Embedded AI. These blocks cumulatively will form a well-designed real-life case study, from setting up the project to the theoretical research, and data processing to modelling and deployment. A group of 3-4 students will work in a team on any of the course projects. As these are highly skilled and talented students, and base on how the course is designed, we expect each of these projects lead to at least one publication.
This year edition has led to the submission of 4 papers for 5 teams and we are having one more paper under preparation.
All projects contain an AI (Artificial Intelligence) or ML (Machine Learning) based solution applied to a variety of application domains:
* Brain neuroactivity and anxiety level in mice
* Gender equality in movies
* Nanoparticle design for cancer therapies
* Web application testing
* Autonomous maritime vessel
You can watch short video presentations of the projects here: https://www.youtube.com/playlist?list=PLZqJR4V7fsuYMx_XF6xSK_9KGD2kPrTMS
In this presentation we briefly present how the course was design, implemented and run. We will showcase some of the course project and we will discuss the potential opportunities to collaborate with researchers from MDU for the next edition of the course.