earned her PhD in Demography from the Max Planck Institute for Demographic Research and the University of Groningen. She is now a Researcher, Research Engineer, and Lab Manager at the at Vrije University Amsterdam. Her work brings together data science and computational methods to study issues like climate change adaptation, older adults鈥� use of technology, and migrants鈥� cultural integration.
Since completing her CAnD3 training journey in 2022, Sofia reflects on how the program broadened her perspective and shaped her approach to multidisciplinary collaboration.
Read on as Sofia shares her experiences during and after CAnD3.
Good morning, Sofia! Thank you so much for joining us for our Alumni Feature Series. To kick things off, what inspired you to join CAnD3, and what were your expectations when you first entered the program?
Thank you for inviting me! I joined CAnD3 because I wanted to be exposed to a different way of thinking.
My background is in actuarial science and computer science, which are very number-driven, and I was looking for a more holistic education that also included the human dimension. My cohort included both quantitative and qualitative researchers as well as social scientists, and being exposed to these diverse perspectives was both important and very interesting for me.
That鈥檚 wonderful to hear. Did the experience align with your expectations?
Yes, definitely. In fact, it went beyond my expectations!
I wasn鈥檛 sure what to expect, but I was looking for an educational experience that I didn鈥檛 have in my PhD program at the Max Planck Institute. It was mostly research-focused there. We had great resources, but not that many courses or teachers. CAnD3 filled that gap, and I really appreciated it.
Building on that experience, how has your career evolved since completing the CAnD3 program?
Since completing the program, I finished my PhD and now work as a researcher and lab manager at the Societal Analytics Lab at Vrije University, Amsterdam.
During my PhD, I worked on using digital trace data to study population dynamics, but now I鈥檓 transitioning to research on generative AI, specifically, how it spreads misinformation and how to design interventions for the general public to raise awareness about the risks.
Congratulations on completing your PhD! Can you tell us about your Applied Research Project during the program?
At the time, I was already working with digital trace data, particularly using Twitter data to study migrant cultural integration. I used this project for my applied project at CAnD3. It was very valuable to share my PhD work with peers and get feedback.
Coming from a STEM background, I sometimes forgot that numbers represent people, contexts, and feelings. The feedback from peers and hearing about their projects was very insightful. I also enjoyed giving crash courses on retrieving and analyzing digital data in a safe, collaborative environment where mistakes were allowed. It helped me learn how to communicate my work more clearly to people outside my field.
How did CAnD3 shape the way you approach your work and communicate your research?
CAnD3 helped me see the value of multidisciplinary and transdisciplinary collaboration. One presentation that stood out was from a Statistics Canada qualitative researcher who explained how focus groups can improve census questions and interpretations.
That changed my perspective, it showed me that qualitative research is just as important, meaningful, and difficult as quantitative research.
Now that you鈥檝e completed the program and some years have passed, what advice would you give to someone considering joining CAnD3?
Be open-minded, eager to learn, and not afraid to make mistakes. Nobody will criticize you for asking questions. It鈥檚 important to share your work and be receptive to feedback, no matter who gives it, it will be meaningful.
Looking back, do you see a clear connection between your CAnD3 experience and your current work?
Yes, definitely! Before CAnD3, I was very focused on quantitative research. The program helped me become more open to collaboration, and I learned how to structure collaborations effectively, defining roles, plans, and goals. This is essential when working with people from different fields.
My current research on AI risks is transdisciplinary and involves collaboration with qualitative researchers, universities, and government agencies. Without CAnD3, and especially without that module on qualitative research, this path might not have opened up for me.
That's great to hear! Now, a fun question to wrap up, if you had to describe your research as food, what would it be and why?
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It's a very good question! I am Mexican, and I鈥檇 say Mexican cuisine is among the best in the world because it blends influences from many cultures. Take the taco: it starts with corn, a Hispanic staple, then incorporates meats like pork and beef introduced by the Spanish, and even techniques like the vertical spit used for tacos al pastor, which came from Middle Eastern immigrants.
So in one taco, you have three cultural traditions coming together to create something unique. I see my research the same way, it brings together different perspectives and methods to create something richer than any one approach on its own. In a sense, I like to think of my work as 鈥渕aking tacos鈥� in research.
That鈥檚 a fantastic metaphor, and a really memorable way to describe your research. Thank you so much, Sofia, for sharing your journey with us and reflecting on how CAnD3 shaped your path. We look forward to seeing where your work takes you next.
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