Mariëlle Stoelinga uses data analyses to predict potential malfunctions
Research
She is fascinated by risks and risk taking. To put it another way, what risks do we consider acceptable and how can we deal with them optimally? As a professor and research scientist, Mariëlle Stoelinga develops methods of ensuring that the risks of high-tech systems remain within acceptable limits. ‘Among other things, I research the risks of high-tech systems that are currently in use and being produced’, she explains. ‘These risks include nuclear power plants, trains, robots and hyperloops. For instance, how do you optimise the safety of trains without giving rise to collisions, malfunctions or derailments?’
Stoelinga’s specific focus area is predictive maintenance. ‘This involves using data analyses to predict malfunctions better, so that they can be prevented.’ One of the measures you can take, is maintenance, she continues. ‘How should the track be maintained – and how frequently – to ensure that all the switch points are working and that the signals change correctly to red and green? We use data to make the predictions. If the track is in good condition, less maintenance is needed than where freight trains run frequently on it.’
Stoelinga chose to study Computer Science because it emerged from a study choice test that she had an above-average interest in all disciplines. ‘That gives you a wide range of potential applications,’ she explains. It gave her a unique position in her field. ‘Risk management is usually viewed from a different perspective. From the viewpoint of finance, for example, or machine construction, mechanical engineering, civil engineering or even social science. I’m one of the few people who study this field from an ICT perspective.’
What does she find so fascinating about risk management? ‘What I enjoy in particular is working with a variety of stakeholders and to look jointly at how we can link specialist fields,’ says Stoelinga. ‘I’m an inquisitive person by nature and love solving puzzles.’ With regard to her views on the future, she sees the need for a much larger multidisciplinary team for predictive maintenance. ‘Our team currently focuses strongly on components, in other words a single part of a system. But the challenge is to monitor entire machine parks. How do you cope with that?’
And finally, there is another topic she would like to mention in addition to predictive maintenance: safety, security and co-engineering. ‘There is often a conflict between safety (malfunctions due to unintended accidents) and cybersecurity (malfunctions due to malicious attacks by hackers),’ Stoelinga explains. ‘Measures for guaranteeing security often weaken the cybersecurity. The trick is to integrate these two fields. To research this, I received an ERC Consolidator Grant in 2019.’
Teaching
Although Stoelinga works mainly as programme manager for the executive master’s programme Risk Management, she also lectures on the master’s course Software Testing & Risk Assessment at the University of Twente. In addition, she has a part-time position at Radboud University in Nijmegen, where she teaches Model Checking. ‘What I like about teaching is that when you explain things to students, you will often come to look at things differently as well,’ Stoelinga says. ‘Questions and new ideas force you to rethink things.’ What would she like to pass on to students? ‘I became a professor because I’m permanently inquisitive. And I hope I can trigger that among students.’ She also considers it important to teach them sustainable skills for the future. ‘So that they will be thoroughly prepared and will be able to learn new techniques easily.’
About
Mariëlle Stoelinga is Professor of Risk Management for high-tech systems at the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente. In addition, she has a part-time position at the Software Science department of Radboud University Nijmegen. She is also programme manager for the executive master’s programme Risk Management, in which professionals are trained to be professional risk managers. In 2019, she received a substantial grant under the Dutch Research Agenda (NWA), as well as an ERC Consolidator Grant from the European Research Council. With the NWA grant she heads a team of industrialists and academics with a view to a better integration of various steps in predictive maintenance. With the ERC grant Stoelinga is developing new methods of making better and more integrated assessments of both safety and security risks.
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