Faculty Spotlight: Nynke Niezink

Nynke Niezink, assistant professor of Statistics & Data Science, works on developing statistical methods for the social sciences. In particular, she focuses on modeling network dynamics based on various types of complex network data.

Tell me about your scholarly work?

I work on statistical models to study the dynamics of networks and individuals embedded in those networks. These models allow researchers to study how people’s behaviors and opinions are influenced by the individuals who surround them. Recently, I have become interested in modeling networks where more than two individuals are involved in a social circle, for example in group action or in gossip. Gossip has a sender, a receiver and a target. Models for the dynamics of three-way networks will allow us to take into account each of those roles.

How is your scholarly work adding to the greater field?

As statisticians, we are in a privileged position in the sense that we can contribute to many different fields. The open source software that I work on with my collaborators has been applied in over 300 papers, by sociologists, educational scientists and criminologists, to name a few, to study how social systems develop over time. I also directly collaborate with scholars from several different backgrounds. These interdisciplinary collaborations in turn often lead to methodological questions, which makes for great synergy.

How did you become interested in this topic?

While studying both mathematics and educational science, I became interested in how we can use graphs to represent social systems. Graphs, or networks, are simple mathematical structures consisting of nodes that are connected by edges, and we can use them to represent real-life systems, like the internet, road networks and body systems, to name a few. The implications of taking on a network perspective on real-world phenomena are really huge. And the complexity of human behavior makes this research area even more exciting.

What are you most excited to accomplish as a faculty member at CMU?

In the coming years, I want to continue to develop tools to help us understand social behavior. I am particularly looking forward to furthering the three-way network methods, which will help us shed light on how people perceive the networks they are embedded in. Network perceptions are known to differ from person to person, but we know little about how perceptions are formed and currently have no tools to study them.

I was also selected to be a Provost’s Inclusive Teaching Fellow at CMU. I want to use this position to make courses accessible for everyone irrespective of their background. I want our students to feel a sense of belonging in the courses being taught in our department. I also want to create a network for undergraduates interested in network research at CMU, extending the networkshop research group in our department to undergraduates. Research is something we do together. I want to create a community for people who are excited about this topic.

What are your goals for the next generation of scholars?

In today’s world, we are bombarded with information. I want to help my students think critically about the information that they get. I want to help them learn how to handle and process all of this information and to challenge the assumptions behind it. As statisticians, we work a lot with data and learn from data. This is an important skill for the students today, in their courses and research, but also in their future careers and lives.

The Faculty Spotlight series features new and junior faculty at the Dietrich College of Humanities and Social Sciences at Carnegie Mellon University. Stay tuned for our next installment to learn more about the dynamic and engaging research and scholarly work being conducted in the college.