How would you describe your work in 90 seconds?

My research focuses on how people interact with digital environments and how these environments shape user behavior and decision-making. I also analyze the content, dynamics, and structure of these systems to assess their impact and develop models of user preferences. This is central to advancing recommender systems and personalized solutions across different domains like media, e-commerce, and tourism, systems that not only empower users but also consider the needs and perspectives of other key participants in the digital ecosystem, from content creators to policymakers. I run the Christian Doppler Lab for Recommender Systems here at TU Wien Informatics, where we work on these approaches. As the UNESCO co-chair on Digital Humanism, I also focus on the broader impact of these systems on individuals and on society. It is crucial to study personalization and recommender systems in the context of filter bubbles and echo chambers to understand their influence on behavior. Our goal isn’t just to improve these systems, but to ensure they can help people rather than just manipulate them or even cause harm. Another key aspect of Digital Humanism is to bring different disciplines together to better understand how digitalization shapes culture and society.

How did you get in touch with informatics?

When I was in school, I computer science classes as an elective. I liked it, and I had a good teacher, but there were very few hours. Later, when I studied mathematics (pure mathematics), I took some introductory courses in programming and computer science. They weren’t mandatory, I just took them out of interest. After finishing my master’s in mathematics, I was looking for something different, something more applied. I did not want to continue in pure mathematics, and I was fascinated by computer science and the fact that you can develop and create systems that have a direct and tangible impact on everyday life. That’s when I had the opportunity to come to TU Wien Informatics and work in the field of data science, which is a mixture of mathematics, statistics, and computer science. Now I develop recommender systems and models to study how people interact with recommender systems and how the systems influence behavior. So, I went from pure mathematics to a more applied area.

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

The field I work in is fascinating because it has very strong connections to everyday life. Recommender systems, or systems of personalization, are everywhere, like on Amazon or Netflix. Today, you encounter personalization on almost every online platform, where people are confronted with filtered information, and people are becoming increasingly aware of this. It’s now completely normal to visit a website adapted to you with your preferences inferred by the system. If two people visit the same website, they might not see the same page or get the same search results, and all of that happens in the background. Public discourse about recommender systems and the impact that they have on society has increased over the past few years, especially as these systems can even be a threat to democracy, a concern that has intensified since the COVID-19 pandemic. It’s a bit tricky because I do basic research while developing systems that have a high impact on society, and these systems also come with negative aspects. That’s why I’m very committed to Digital Humanism. Although these systems can pose some dilemmas, I am convinced we should continue researching them at university, and not just leave it to big companies to develop those systems. As a university, we have a critical role in thinking about how these systems can be improved. We consider how they can support people and reflect other values beyond just increasing profit. So, there’s an immediate connection between real life and my work.

What makes you happy in your work?

I am happy to work in an area that has a real-world impact. It has a lot of practical relevance, but there’s still so much to do and so many things to explore and focus on. You can bring in more perspectives and collaborate with other disciplines, which helps make the research even better. We have the chance to shape this technology, and there is still great potential to develop it in a positive way. It also makes me really happy to work with students, seeing how motivated they are and what can be achieved, even in master projects. There is so much happening right now that it’s hard to keep pace, but it is also incredibly exciting. For example, generative AI and LLMs are being increasingly used in my field. However, whether they represent a true paradigm shift in the core techniques that we use is still not clear. My work also involves many disciplines and is very international. We have collaborations all over the world, which I really enjoy.

Why do you think there are still so few women in computer science?

This is something that really bothers me, and when I was studying mathematics, we were asking the same question. Together with a colleague, student representatives, and the faculty, we developed a program to promote women in mathematics. In computer science, we have the same issue. Many factors contribute to this, including persistent stereotypes that math and computer science are for boys, a lack of role models, and societal biases that start at an early age. Even today, the number of female students remains low despite many various efforts. Initiatives like workshops that introduce computer science to schools, such as the efforts by TU Wien Informatics with eduLAB, are crucial, but they need to start early. As a mother of a young daughter, I think about how to ensure that she isn’t overly influenced by all these stereotypes, as children are naturally curious and open before biases take hold.

When I started working at TU Wien Informatics, students who wanted to enroll in computer science had to write a motivation letter, followed by an interview. Young men from an HTL (ed. note: a technical high school with a focus on STEM subjects) saw computer science as a natural next step since they already had programming experience. In contrast, many young women from the gymnasium (ed. note: high school) felt the need to justify their interest, as if they didn’t fully belong. Changing this perception is critical. We need to communicate more about how diverse computer science is and emphasize that everybody belongs here. This field is incredibly broad, with many research areas and applications, and this is what I love about it.

Julia Neidhardt is Assistant Professor of Data Science at TU Wien Informatics. She is head of the Christian Doppler Laboratory for Advancing the State-of-the-Art of Recommender Systems in Multi-Domain Settings, and holds the UNESCO co-chair on Digital Humanism.

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