Vor seinem Ruf an die Universität Wien war Han van der Aa Juniorprofessor an der Fakultät für Wirtschaftsinformatik und Wirtschaftsmathematik der Universität Mannheim (2020-2024) und Alexander von Humboldt-Stipendiat an der Humboldt-Universität zu Berlin in der Arbeitsgruppe Datenbanken und Informationssysteme (2018-2020). Den PhD im Fachbereich Informatik schloss er 2018 an der Vrije Universiteit Amsterdam ab. Seinen akademischen Weg begann Han van der Aa mit einem Bachelor in Wirtschaftsingenieurwesen und einem Master in Wirtschaftsinformatik an der Technischen Universität Eindhoven.
Welcome to the Faculty of Computer Science! We hope you have settled in well in Vienna! What is your impression of the city and the university so far?
Thanks a lot! Although I officially started in February, it has now been about two months since I moved here. I am excited to be in Vienna, a city that I have been very fond of since I spend a summer here in 2013, getting my first research experience abroad.
I’ve had a really good first impression of the university as well, with great and helpful colleagues. A point that particularly stands out for me is the wide range of topics on which there are experts here. Working on process mining, a field that overlaps with a lot others, provides a lot of collaboration potential, both within and outside of the Faculty of Computer Science.
You initially studied Industrial Engineering. How did you become interested in Computer Science? What fascinates you about it?
Indeed, I have a bachelor's in Industrial Engineering from the Eindhoven University of Technology. The program itself already included various computer science and information systems courses, which grabbed my interest. This led me to get my academic minor in computer science, and afterwards transition into a master's in Business Information Systems. I think what most attracts me to this direction is the ability to solve complex (real-world) problems through technology. Particularly also the way in which this is achieved through abstraction and breaking up larger problems into smaller parts. These aspects also form the core of what we do in our field of expertise when it comes to organizational processes.
Can you describe your own research in one sentence?
My research focuses on the data-driven analysis of organizational processes, aiming to uncover and improve how people conduct their work.
Where do you see the connection between your research and everyday life?
Processes are all around us and we interact with them all the time. Even if you are not always aware of it, most work being done contributes to some kind of process. Furthermore, we are also all customers of processes on a daily basis, whether it is during a trip to the grocery store, eating at a restaurant, or when ordering products online. So in short, we work on topics that affect our daily lives.
What has been your most challenging research project to date and why?
That's a difficult question to answer, since each research project comes with unique challenges. Still, in terms of content (and hours spent staring at a whiteboard), I would say that my first work on the topic of privacy in process mining was among the most challenging, because it involved a completely different, statistical perspective on the data that we work with.
What was the most personally significant insight or realization you gained during your time as a researcher?
That you need the right mentor(s) to support you in your academic career. Such a mentor doesn't necessarily have to be your supervisor and goes far beyond having someone who comments on your manuscripts; rather you need someone who can provide guidance in all facets of an academic career, such as how to set goals and deal with difficult situations or setbacks. Luckily, I have been very privileged in this regard, thanks to excellent PhD supervisors at the VU in Amsterdam (Hajo Reijers and Henrik Leopold) and a great mentor when I was a post-doc at the Humbolt-Universität zu Berlin (Matthias Weidlich).
Do you have any research plans for the coming years in Vienna?
I am currently setting up my research team here (applications are welcome!) and establishing collaborations with researchers in other domains, as well as with industry partners. So for sure, there are many interesting things to come!
What motivates you in your daily work?
I really enjoy the problem-solving and collaborative aspects that play a role in most parts of the job; whether it is as a researcher working with others to tackle interesting challenges or as a lecturer trying to teach such skills to students.
When you think back to your time as a student, which courses did you enjoy the most? What is important to you in your current role as a teacher?
Topic-wise, I preferred courses that were about solving problems over more theoretical ones. In terms of teaching, I think a main factor is that a teacher conveys their interest in the material; if they are excited about something, students will be, too. I try to take both of these aspects to heart when it comes to my own teaching as well.
If you could change one thing in the academic environment in general, what would it be?
We have to reduce the uncertainty in academic careers. Currently, it takes a long time, with lots of unclarity for researchers, to obtain a permanent position – if they manage to at all, especially in a location of their choice. I should already consider myself lucky to become a tenured professor at my current age (and in a great city!), but even that involved 10 years of temporary contracts in different locations and countries, not knowing where I would be going next. For many others, the situation is much worse. This is highly discouraging and results in a lot of talented people leaving academia or moving to countries with a better tenure system. Particularly worrisome is that, I believe, this situation disproportionately affects women, resulting in further undesirable imbalances.
Why do you think there are still fewer women in Computer Science than men, and what can we do about it?
Unfortunately, I think that there is still a stereotypical perception that certain topics are more suitable for men and others for women, with the view of technology as masculine prevailing in our culture. On the positive side, there are also clear exceptions to this trend. For example, there are countries with a much more equal gender distribution among computer science and STEM studies in general, showing that the gender imbalance we observe here is not a natural given, but rather a cultural phenomenon that may change. Furthermore, one can see that certain courses within our Computer Science curriculum have more balanced gender distributions than others. From my experience, this particularly applies to analytics and data science topics. For instance, my lectures on Business Intelligence have a clear female majority. In the short term, I think it could thus help to understand which kinds of courses attract more female students (and why), so that these can gain more prominence and promotion. In the long run, we need to get rid of the stereotypical perceptions around computer science (and other technical fields of study), but I don't dare to claim that I have a solution for that.
What advice would you give to today’s first-year students?
It's a cliché (and also something that took me a while to reach that point myself), but try to find topics that actually interest you, so that you are studying to learn something, rather than studying just to pass an exam. Once you reach that point, things become much more enjoyable, and results will follow naturally.
