In 2016, important actors from science, industry, and politics founded the Cyber Valley Consortium, which became the first Innovation Campus in Baden-Württemberg. Ten years on in 2026, we’re revisiting the most important milestones from the last decade. Each month, we’ll focus on a particular year since Cyber Valley’s beginning.
This month, we’re looking back to 2018, when the first Cyber Valley Research Groups were established. One of these research groups was led by Caterina De Bacco: between 2018 and 2024, she led the Physics for Inference and Optimization group at the Max Planck Institute for Intelligent Systems before becoming an Associate Professor at Delft University of Technology.
In the following interview, she explains how Cyber Valley’s network of scientists and innovators provided a thriving environment for her research, and how her research could be used for managing traffic in transportation networks.
What were your research group’s main aims and outcomes?
In my group, we were combining expertise from physics, mathematics, and statistics to effectively model complex systems; systems made of many individual elements that interact in complex ways, often referred to as networks. Our research approach aimed at developing mathematically rigorous models to learn patterns from network data or to optimize the design of these systems. We studied applications like clustering, anomaly detection, or optimal transport on networks, spanning various domains, in particular, the social sciences and engineering.
How did your research address real-world challenges, and what kind of applications or long-term benefits could it have?
Learning patterns from network data has applications in a variety of domains, as network data is ubiquitous. One of the challenges is to perform these inferences efficiently. Hence, special focus is given to the development of interpretable and principled models that are also computationally efficient, so that practitioners such as social scientists and engineers can use them without needing large resources, making these tools accessible to a wider audience. All the models we developed have a corresponding open-source implementation of the codes available online. With our models, practitioners can detect hidden clusters of similar nodes from network data or estimate the likelihood that certain observations are anomalous.
In addition, our research on optimal transport has natural applications in managing traffic in transportation or communication networks. With our models, we can design optimal networks that can be used by network managers to assess the efficiency of existing transportation infrastructures.
Cyber Valley is a network of leading research institutions, industry partners, and start-ups working in AI and robotics. How did being part of this network shape your research, skills, or career path?
The exposure to this diverse network of experts was beneficial for the creative process of stimulating ideas, ideation. You have the feeling that there is always something cutting-edge going on around you, and you are among the first ones to know. There are not that many ecosystems connecting research and technology at this high level, so being immersed in it gives you valuable stimuli and ideas.
The Cyber Valley Research Fund was also an important support for advancing our research (I obtained two grants from it). With little administrative burden and a smooth application and reporting process, I could focus mainly on the research itself, in contrast to other mainstream funding opportunities, where you end up spending much more time on non-research-related activities. As a result, our research thrived during these years, with an even higher level of productivity than we originally planned.
How did your experience as a Cyber Valley Research Group Leader prepare you for your next career step?
The opportunity to combine freedom and resources was unique and extremely valuable. This allowed me to grow in several aspects that are important for an academic career beyond pure research, for example, managerial responsibilities. Being able to independently manage a budget and to make key decisions (such as recruiting, deciding how to contribute to teaching) gives you a sense of responsibility and agency that makes you grow significantly faster compared to other young academics who are not as independent. As scientists, we are required to take on different roles (managers, mentors, supervisors, teachers, accountants, fundraisers) that we must learn on the job, as we are usually only trained in the science itself. To be able to effectively learn all these skills, I needed to be given the opportunity. The independence and support I got from Cyber Valley were key in this respect.
As a result, I could start my next career step (as an Associate Professor at Delft University of Technology) with a significant advantage in terms of experience, compared to my peers. Needless to say, being a Cyber Valley Group Leader played a big role in increasing my chances of finding the right job for my next career step.
