Biography

I am a transdisciplinary scholar with roots in computer science applying scientific computing for geography, human cognition, computational social science, mobility, architecture, urban planning, public health, personalised medicine, and renewable energies. My research objective is to design digital twins as practical scientific computing platforms to address the most pressing questions of our time. Digital Twins are crucial to mitigate crises ranging from global climate change to equity, mobility, and health because they allow to improve the efficiency and liveability for humans in cities, building and work environments. I approach my digital twin research through a data-centric lens, investigating how the data life cycle of data acquisition, data management, data analysis, and ultimately data value extraction can be best achieved. Digital twins enable smooth interaction with data in any stage of its life cycle helping across disciplines to communicate with scientists, governments, industries, and the public. As researchers, we also have a holistic duty to ensure that the data and its processing is reproducible. I am a staunch supporter of Open Research Data (ORD) and I aim to advance the reproducibility of scientific work with digital twins thereby making data more relevant for policymaking. In my current research, I am making urban mobility analytics more accessible to both researchers and a wider audience through applying the FAIR (findable, accessible, interoperable and reusable) principles to digital twins. I am combining applied spatial data science with foundational research by capturing the complexity of real-world mobility to develop informative models for experts and laypeople alike.

I am a strong proponent of research-led teaching. To engage in science, teaching is as important as research and often both can be enhanced by integrating them with each other. Students are not only equipped with knowledge, experience and skills but are also contributing to the body of science and they develop a sense of belonging by taking ownership of their work. To lead students in research-led teaching requires a strong level of engagement, empathy, and interaction. The classroom should motivate and inspire students to independently explore questions and provide them with the tools to start working on them. At the same time, critical thinking needs to be stimulated to realize the limitations of any method and approach. Personally, I was in the lucky position to become a cognitive scientist by experience through research-led teaching. As a student researcher at the Cognitive Science Group at ETH Zürich, I was involved from the get-go in real research. I was encouraged to ask questions, question any procedure, to apply my Computer Science skills in a new context, and learn about Cognitive Science through my tasks. I hope to impart this experience to my students and inspire them just like I was.