Assistant Professor Mikko Kivelä studies multilayer networks

The aim is to describe certain, more complex phenomena more realistically than before.
Picture: Lasse Lecklin

Assistant Professor Mikko Kivelä, what kind of research do you do?

My starting point is the theoretical research of phenomena that can be modelled as networks. These include social, gene regulatory and transportation systems, which can be described as interlinked elements. From the theoretical perspective, all these networks look similar and share the same kinds of phenomena and analysis methods. My goal is to further develop these methods for researching complex systems and networks.

I specialize in multilayer networks that can be used to describe larger phenomena more realistically than before. These types of networks can include information on, for example, several different types of nodes and links, or they can be used to combine multiple networks.

If a network describes, for example, social contacts, the relationships between people and the links that describe these relationships will, in most cases, differ from each other as well as dynamically change. For example, one network might describe how people are in physical contact with each other, while another network characterises the communication between them. Because these networks are, of course, not independent of each other, they should not be researched separately, either. Multilayer networks are also referred to as, for example, "networks of networks" in literature.

Network science has many applications. Among other things, networks make it possible to model spreading phenomena more effectively, such as the spread of a disease or information in social networks. Seen from a multilayer network standpoint, a disease and information on it spread in different networks, with each network and the spreading process being interlinked.

How did you become a researcher?

I started out as a research assistant at the Helsinki University of Technology in 2006, because I was interested in working as a researcher and in network research itself. Network science and my own research have made huge strides since then, but, for the most part, the research problems, methods and paradigms we encountered back then are very similar to what we have today.

I earned my doctoral degree in network science at the Aalto University Laboratory of Computational Engineering in 2012. My doctoral adviser was Professor Jari Saramäki. I did my mandatory civil service at the University of Helsinki, working with bioinformatics and cancer research.

What is the highlight of your career?

In 2013-2015, I was a postdoctoral scholar at the Mathematical Institute at the University of Oxford. Oxford is a vibrant environment, where you'll find top researchers in a wide variety of fields from all over the world. A large percentage of the city's residents are involved with the university in one way or other, and there was virtually always some interesting, science-related things going on there.

What is the most important quality for a researcher?

As your career progresses, an emphasis is generally placed on having vision, while for researchers, technical expertise is stressed at the beginning of your career.

What is the most important thing that you want your students to learn from you?

I'm always ready to encourage them, sparking their interest in the field and teaching them an independent approach to working as a researcher, and also getting them to bravely try new approaches and spread their wings.

What do you expect from the future?

My goal is to establish my own research group and recruit suitable doctoral and Master's students. Right now, I'm supervising two doctoral students who are about to graduate. I am very excited about implementing my own long-term research plan on multilayer networks.

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