How would you describe your work in 90 seconds?

I work in biomedical visualization and visual analytics. In this domain, we support experts, like clinicians, bioinformaticians, policy makers, but also lay people, to understand complex, multidimensional, heterogeneous data coming from the biomedical field. This can be medical images or genomic information. The idea is to take complex data and to create a visual representation out of it, so that the intended audience can understand it, can get some insights. Visualization and making medical information understandable and accessible play a big role in the healthcare domain.

How did you get in touch with informatics?

I did my diploma in electrical and computer engineering in Greece, and it was during my studies that I first came into contact with biomedical engineering. Once I finished my diploma, I thought, OK, I don’t want to do anything with informatics, so I went to study biomedical engineering in the Netherlands, at TU Delft. I had some courses on data visualization and medical visualization, and there was a very charismatic and motivating professor, Charl Bota. He inspired me to stay in the domain, and that’s how I returned to informatics. I was working on the topic of uncertainty visualization, and I remember that he was saying, oh, can you make sense out of this data? That’s when I realized that visualization is fun, and it’s much more than just pretty pictures - you have to have a very strong background in computer science. I had to give a talk some years back, and I described my career as a chaotic attractor. A small perturbation can make you end up on a very different path. I started out with informatics and computer engineering, then I went to biomedical engineering, and then I went back to informatics. I’m happy with how it turned out.

What makes you happy in your work?

I particularly enjoy that my work can make a difference. I work with clinicians and bioinformaticians, but I also work on solutions for laypeople. When I’m working with clinicians and other domain experts, I like the moment when they see something for the first time in their data, or something that they were initially not aware of. You can help clinicians make a decision faster, better, or easier, and help them detect risks for their patients early on. Part of my work is teaching and mentoring students, and that may be the part that I enjoy the most. It keeps me young; that’s the part I really like (laughs). Every semester, I see students starting out very confused. I enjoy seeing their curiosity, their progress, seeing them grow, and how their interests evolve throughout their studies and projects. Another important reason why I chose the field of biomedical visualization is because of the societal impact that it can have, especially in the healthcare sector.

Where do you see the connection between your work and everyday life?

I see my work as a bridge between abstract data and decisions or actions. In the beginning, you have a whole bunch of data and information that you cannot make sense of; it’s very complex and messy. Take, for example, clinicians and radiologists; they need visualized data every day, not for academic exercises, but for saving lives and improving our well-being. I think there is a growing need to support the healthcare sector. We saw that during the pandemic, and we also see that with infodemics that concern experts as well as the general public. They are increasingly overwhelmed by a huge amount of information that they do not know what to do with. It’s our duty to empower them with knowledge, to try to democratize this knowledge, and to help them make sense out of this whole process. We often talk about big data, and right now, we are advocating human-in-the-loop, artificial intelligence-based approaches, where we try to get the best of the AI domain and the best of the human input to do a little bit better than traditional methods would do.

Why do you think there are still so few women in Computer Science?

There are still a lot of stereotypes, and maybe the lack of exposure to it at a young age. I come from a family where I never heard that, oh, girls cannot do this, girls cannot do that. It was about what I was interested in, and I really liked math. We should also acknowledge that a lot of things are happening; we keep saying that there are very few women in computer science, but I see a huge improvement. When I was studying, a bit less than 20 years ago, I was in a class of close to 200 people, maybe more, and it was only 15 girls. That is not the case anymore, and to see these changes is very motivating. I believe that our faculty is doing a lot to push in this direction. We have fantastic examples of female researchers in our faculty who are doing cutting-edge research with real impact. I think this helps younger students to see that it is also possible for them. There is one more thing that I think matters for all genders - if you have really outdated curricula that are not relevant and that don’t allow for any playfulness, students are not going to enroll.

Renata Raidou is Associate Professor at the Research Unit Computer Graphics at TU Wien Informatics. Her current project, Health virtual twins for the personalised management of stroke related to atrial fibrillation (TARGET), aims to the prevention, management, and rehabilitation of atrial fibrillation-related strokes by developing personalized computational models and decision aids for improved patient outcomes. The project is funded by the Horizon Europe program and is set to run until 2028.

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