Take 10 with... Hyesop Shin

1. Describe your research topic to us in 10 words or less.

Simulating heterogeneous agents to understand complex urban system behaviours.

2. Now explain it in everyday terms!

I enjoy running models, particularly something called agent-based modelling (ABM). Here, an ‘agent’ can be anything created in the virtual world. It could be a person, a car, or even a tree. Doing ABM is very exciting because the idea is to understand the process of how different (heterogenous) people move across space and time.

3. Describe some of your day-to-day research activities.

As a dad of two children, my day always starts early. Before the kids wake up, I tackle the reading or writing tasks relevant to my teaching. Once I’m on campus, I’m focused on supervising students, giving lectures, going to labs and administration. On a day where my calendar is clear, I sometimes hop on to my programming codes to see what I can improve (psst, these days, I'm working on a package that's compatible with both R and Python).

4. What do you enjoy most about your research?

I would say the ‘what if’ question. With all the possible assumptions inside the model ecosystem, I sometimes hypothesise extremes and reflect on these. Even if real-world data is absent, imagination feeds into research too. I believe that all models have their purposes. Some are designed to be precise enough to predict and explain social phenomena, while others are more abstract. Recently, my focus has been on the effects of congestion pricing on traffic patterns and whether it would change people’s behaviours and transport mode choices.

5. Tell us something that has surprised you in the course of your research.

When I was working on a participatory research project with OpenStreetMap, I often wondered who would dedicate their own time to contribute. From the survey, I was astonished to discover that one of the top ten contributors was a 75-year-old woman. We also found that a few people were editing maps late into the night. I was surprised and inspired to see that the free, crowdsourced data we rely on is built by such a diverse and anonymous community of volunteers.

6. How have you approached any challenges you’ve faced in your research?

At the beginning of my second year as a PhD student, I was ready to publish my first paper. Just before submitting the final version, my supervisor asked to review my model code. I shared the GitHub repository confidently, but a few days later received the alarming message that the code did not perform as described and might require a major rework.  The excitement of being nearly published collapsed into deep frustration. To resolve this, I went back to the model, recalibrated, rewrote and tested everything, a process that delayed the paper by nine months. Through this trial, I learned to be patient, transparent and resilient in facing setbacks.

7. What questions have emerged as a result?

This experience made me reflect more deeply on the process of modelling itself. How do we ensure transparency and reproducibility in computational research when such small coding errors can alter entire conclusions? More broadly, it made me question how much scientific progress comes not from perfect runs but from the lessons embedded in failed attempts, and how we can better embrace error as part of the research process. This was a tiny coding error, but its impact on my learning was huge, even if nobody recognised it. It taught me that research integrity lies in the willingness to confront, correct and share the lessons arising from mistakes.

8. What kind of impact do you hope your research will have?

In my congestion pricing project, the research is highly transdisciplinary. I collaborate with colleagues across engineering, public health, and urban design, as well as council partners to create synergy between academic and policy perspectives. While this kind of work takes time, it reflects the reality that social challenges are deeply interconnected. I hope my research will contribute to more benefits across multiple sectors and communities.

9. If you collaborate across the faculty or University, or even outside the University, who do you work with and how does it benefit your research?

At the University, I collaborate with Jamie Hosking in FMHS on health equity and air quality impacts of congestion pricing, Melody Smith in FMHS on greenspaces and children’s physical activity, Minh Kieu in Engineering on combining large language models with traffic microsimulations, and Wendy Liu on urban policy. Beyond Auckland, I also work with a dedicated group in Scotland on Low Emission Zones. Through my years as an early career academic, meeting these people feels like a blessing – all are professional and lovely!

10. What one piece of advice would you give your younger, less experienced research self?

Panic doesn’t help you progress, and always respect your peers and students.