How can we work more efficiently with data delivering higher quality software? 

Software development and software based systems rely increasingly on high quality data. How can we work more efficiently with data delivering higher quality software? 

This year’s theme for Software Technology Exchange Workshop (STEW) is Data for Software Development. The conference program is filled with presentations where industry, academia and public sector presents different perspectives on the theme as well as workshop parts where the participants will be able to discuss the subject. You will be able to engage in discussions and listen to presentations such as; Visual software analytics: challenges and opportunities, Explainable artificial intelligence for predictive maintenance and The petabyte project.

A place to find new inspiration and connect with people facing the same challenges

Sven Nilsson is a software innovation specialist in X Innovation Lab at Radar Solutions, which is a part of SAAB. During the past couple of years, SAAB has done many promising tests and prototypes in the realm of machine learning and AI. This year, X Innovation Lab has tried to take one of those promising ideas from the test bench to an actual product, running live and delivering customer value.

My talk at STEW is about the journey we are currently taking towards implementing and delivering functionality based on machine learning within a defense context says Sven. Like so many before us, we found that it takes a lot more than a neural net to make AI work in the real world. In this talk, I will describe how we have tackled the lack of quality data, the need for safety and predictability in a defense environment and the problem with aggregated data from a secrecy perspective.

Conferences like STEW are very important as a place to find new inspiration and connect with people facing the same challenges I you do. This year it is even more important, since most of us have been sitting at home since the pandemic started.

Sven Nilsson, software innovation specialist at SAAB AB gives an introductino to his talk at STEW – The Petabyte Project.

Learn from each other

Rafael Martins is a Senior Lecturer in Computer Science and Media Technology at Linnaeus University, in Växjö. His main research work is in the area of Visual Analytics, which is somewhere in-between Information Visualization and Data Mining, with a little bit of Machine Learning. Rafael is interested in enhancing analysis pipelines for large and complex datasets by putting the human in the loop (as we say), so that analysts can interact with their data using effective visual interfaces.

At STEW Rafel will talk about the role of visual analytics in software development, by going through some recent examples of interesting proposals and works in the area. Software development is one prominent domain where visual analytics can lead to very interesting results, because it is both a data-driven process and also heavily human-centered. These two characteristics, when they happen together, usually become a fertile ground for visual analytics approaches.

I think the main attractive of STEW is that it involves both people from academia—professors and researchers—and also those from the industry, so it ends up being a very fruitful exchange for both sides says Rafael. Rafael continues: I think both these perspectives are different and important individually, but when they come together (in an event like STEW) that is really the ideal situation, so we can learn from each other.

When it comes to visual software analytics, I think the greatest benefit here is that I believe that it is the kind of concept that is still in its infancy when it comes to practical applications. There is some kind of barrier, currently, that we need to break down in order to make sure that the cycle of technology transfer from academia to industry starts happening, and I hope to contribute a little bit to that.

Rafael M. Martins, PhD, Senior Lecturer in Computer Science and Media Technology, Linnaeus University, gives an introduction to his presentation Visual software analytics: challenges and opportunities .

A platform to spread knowledge further

Slawomir Nowaczyk is Professor in Machine Learning at Center for Applied Intelligent Systems Research (CAISR) at Halmstad University. The Center focuses on (semi-)autonomous knowledge creation and development of aware intelligent systems; in other words, constructing systems that can handle events that are unknown at the time of design.

At the Center we research how to design systems that, as autonomously as possible, discover new knowledge and insights in real-life data, often streaming data, created through the interaction between a system and its environment says Slawomir. Our research covers many different applications, from the automotive industry, through smart energy and smart cities, all the way to healthcare and health technology, Slawomir finishes .

In his presentation, Slawomir will talk about a scenario where Machine Learning is used to solve an important problem: Predictive Maintenance. As machines and systems are becoming increasingly complex, it is more and more difficult to identify problems that are developing; in particular, to do it sufficiently early to guarantee continuous and efficient operation. Artificial Intelligence and Machine Learning are widely used for that; however, in most cases, it is the black-box models, often based on deep learning. Unfortunately, the decisions made this way are often difficult for human experts to understand – and therefore, to act upon. Operators, technicians and managers require insights to understand what is happening, why it is happening, and how to react. The effectiveness of the Predictive Maintenance depends less on the accuracy of AI alarms than on the relevancy of actions performed based on them.

Events like STEW are a crucial opportunity for scientists like me to disseminate information about our research. Most research at CAISR is done in very close collaboration with partners from the commercial and public sector, which guarantees that it addresses real problems and provides realistic, feasible solutions — however, in many cases, it is only our most direct partners who benefit from that. STEW is a platform that allows us to spread this knowledge further, and to establish new collaborations for the future, hopefully says Slawomir.

Slawomir Nowaczyk, Professor in Machine Learning, Halmstad University, gives a short introduction to his presentation Explainable artificial intelligence for predictive maintenance. 

If you want to know more about all the STEW 2020 speakers and presentations, you can find the program for STEW here.

Make research and project results visible and available to stimulate new cooperation in software technology

Besides listening to interesting and inspiring speakers, the conference offer many opportunities for virtual discussions as well as workshops with all participants. You will also be able to sign up to participate in digital networking during lunch and coffee breaks.

At STEW we want to make research and project results visible and available to stimulate new cooperation in software technology.

You will be able to get to know about new research and build your network – we hope to see you in January!


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