Vera van Zoest is queen of data

In the methods course you will meet Vera van Zoest for the first time. She teaches statistics at the master's programme Innovation, Defence and Security – and over your two years with her, she wants you to become a critical thinker.

Specializes in methods for data analysis and statistical modelling

In Vera van Zoest research, she specializes in methods for data analysis and statistical modelling, that extends to the spatial and temporal domain and can help create predictions. Specifically: Applications that are of interest for crisis management.

Please tell us a bit about your background and your first academic steps!

"I was born in the Netherlands, where I studied during my bachelors, masters, and doctoral studies. I have a bachelor in Spatial Planning and a master in Geo-Information Science, both from Wageningen University. I did my PhD at the University of Twente, focusing on spatial statistics for modelling sensor data in Internet-of-Things. We used data from air pollution sensors to map and predict air pollution."

At what point did you come to Sweden – and to the Swedish Defence University?

"I moved to Sweden in 2019, where I did my postdoc at the IT department at Uppsala University. There, I focused on data analysis and machine learning for smart cities. Everyone has data nowadays, so my competences in data analysis were widely asked for."

"That’s how I ended up being involved in a wide variety of projects, related to for example energy and epidemiology. During the pandemic, for example, we tried to predict how COVID-19 would spread between different neighbourhoods in Uppsala Län."

Applications that would be of interest for crisis management

"Last year I received funding for my own research project focusing on the effects of the pandemic on electricity consumption. This project has been published on the IVA-100 list 2023, highlighting projects with a high societal significance. In September 2022 I started at the Swedish Defence University."

Your methods for data analysis and statistical modelling are extremely relevant to the field of Defence systems. Please tell us a bit about what you do.

"I am focusing on applications that would be of interest for crisis management. For example, we would like to use big data and machine learning models to predict energy crises and predict people’s electricity consumption behaviour in times of crisis. We would also like to make simulations of the electricity network to detect any vulnerabilities which could be the cause of an energy crisis."

What fascinates you about the field of systems science for defence and security – and why should your students be equally fascinated?

"We who teach at the master's programme Innovation, Defence and Security have a very broad focus on war, crisis, and security. I very much appreciate the socio-technical approach we take, including the interactions between technical systems and their users."

How social aspects and behaviour play a role in crisis situations

"I take the same approach when studying energy systems: the grid has its technical vulnerabilities, but there are many social aspects which also play a role. For example, how people’s behaviour in times of crisis can suddenly change, which can lead to worsening of crises. We have seen that during the pandemic when people started hoarding toilet paper, and during financial crises when people start taking out their money from the banks. The same could happen in times of an energy crisis when people start “hoarding” energy."

"I like working with quantitative data, and statistics provide an objective way of analysing data. I teach introductory statistics, for example on correlation, regression, and hypothesis testing. For example, we study the relations between two variables."

Data has a spatial and temporal location

"Most data we gather has a spatial and temporal location – data is collected at a certain location at a certain time. In teaching we focus on simple statistical models, but in my research, I extend these to the spatial and temporal domain. For example, how a crisis at a certain location and time stamp is related to previously occurring events in nearby locations."

How would you describe the societal applicability of your field of research?

"In research, we always try to be at the forefront of what is happening in the society. That’s the great thing about statistical methods, they can be applied to different topics depending on the needs in society. For example, I previously studied the spatio-temporal spread of infections during the COVID-19 pandemic, and we tried to predict infection hotspots during the peaks of the pandemic."

"Over the last year, I studied the effects that the pandemic had on our electricity consumption patterns, for example as a result of more people working from home nowadays. Now, the war in Ukraine has turned our focus on the energy crisis in Europe, and we try to predict what happens there."

AI, big data and data quality

What is challenging within your field of research?

"Now we live in a digitalized world where a lot of data is being collected, and we face the challenge of making sense of large datasets. We have all heard about artificial intelligence (AI) and how that affects our daily lives. But we must be extremely careful when using large models based on big data, as they are too big to comprehend and therefore vulnerable to biases."

"I put a lot of focus, both in teaching as well as in research, on data quality evaluation. I think it is important to teach students to be critical to their data sources and look for any outliers in their data."

How do you balance your teaching responsibilities with your advanced research?

"Teaching introductory statistics forces me as a teacher to take a step back and really reflect on what the essential parts are and how to convey these to the students in a simple and instructive way. This has not only improved my teaching and made statistics more accessible to students but has also helped me to reflect on how to write my own academic papers in a clear and instructive way."

"Vice versa, my research provides me with examples to use in teaching. Students really appreciate using examples of events that they can relate to, for example the pandemic and the energy crisis."

The importance of critical thinking

What “life lesson” would you like your students to take away from your teaching?

"I want my students to become critical thinkers. After my lecture on statistical significance, I want my students to look differently at all statistics, political poll results etc. they are presented with in the news, and question whether any differences are statistically significant. Whenever they see graphs, to look at the scales of the axes and wonder whether someone has been playing with the visualization to convey a different message. And whenever they get data to work with: to first assess the data quality critically before running blind analyses in a black box."

What aspect of teaching do you enjoy the most?

"I become very happy when students ask questions, especially when they ask good questions. It shows that they understood what I was talking about, and that they try to understand even more. It shows their motivation, and of course that makes me as a teacher more motivated too. In our master program we have relatively small groups of students, which creates an informal atmosphere in which students dare to ask questions. This makes teaching much more fun."

Makes statistics accessible and fun

"Many students are afraid of statistics when they start the Methods course. I try to do my very best to make statistics accessible and fun for everyone, and the students really appreciate that. We have a mixed group of students with different backgrounds, so I like to start with the basics, to make sure everyone is at the same level when we continue."

"We want to give the students a lot of hands-on knowledge and a toolkit for them to learn how to develop themselves in their future career. But given the breadth of the program, we only have a limited time do cover each topic. Therefore, I focus on those things they practically need in their future careers, skipping theoretical proofs, but rather giving lots of examples."

"Depending on the type of career they choose, they will need different skills. We cannot teach them everything, but instead it is important that we as teachers provide students with the tools to “learn how to learn”, so that they can become independent learners."

What would be your best advice for your students, related to their academic work?

"Be a critical student and use the opportunities you get to ask questions."

What do you do in your spare time?

"We live on a small horse farm on the countryside with our two horses. After sitting behind my computer all day long doing research, I enjoy some physical exercise on the farm, doing some renovation work, gardening, or riding the horses."

More about the international Master's programme Innovation, Defence and Security