Mikko Kivelä

Assistant Professor
Assistant Professor
T313 Dept. Computer Science

I am a network scientist working as an assistant professor at the Aalto University, where I also obtained my doctoral degree. Before coming back to Aalto I was a postdoctoral scholar at the Mathematical Institute at the University of Oxford.

My research area is the relatively new field of network science (or complex networks). This means that I'm interested in complex systems with a large number of elements that are interacting with each other in some non-trivial way and possibly leading to some emergent phenomena. Social systems are a good example: they consist of multiple elements (people) that are interacting with each other (social relationships) and lead to some very complex emergent behaviour (social groups, societies, conflicts, etc.). Other such complex systems include transportation systems, gene-regulatory systems in cells, ecological systems and many more. I see all of these systems as networks that can be studied with the similar sets of tools and theories.

All of the above-mentioned systems, and many others, have been studied extensively using networks where the nodes (people, cities, genes, ...) are either connected by a pairwise link or not (friendship, road, regulatory relationship). This approach has been extremely successful. However, this abstraction discards a lot of important information about the system. For example, social networks have multiple types of relationships of varying strengths and they are inherently dynamic. Including such information greatly increases our understanding of these systems and processes on them, for example, how disease spreads on social networks. These types of more realistic networks are the focus point of my research.

Full researcher profile
https://research.aalto.fi/...

Contact information

Phone number
+358503824555

Areas of expertise

Social networks, Complex systems, network science

Research groups

  • Computer Science Professors, Academy Research Fellow
  • Computer Science - Complex Systems (Cxsys), Academy Research Fellow
  • Professorship Kivelä Mikko, Academy Research Fellow

Publications

Reticula: A temporal network and hypergraph analysis software package

Arash Badie-Modiri, Mikko Kivelä 2023 SoftwareX

Investor trade allocation patterns in stock markets

Kęstutis Baltakys, Juho Kanniainen, Jari Saramäki, Mikko Kivelä 2023 Journal of Economic Behavior and Organization

Estimating inter-regional mobility during disruption: Comparing and combining different data sources

Sara Heydari, Zhiren Huang, Takayuki Hiraoka, Alejandro Ponce de Leon Chavez, Tapio Ala-Nissila, Lasse Leskelä, Mikko Kivelä, Jari Saramäki 2023 Travel Behaviour and Society

The Unreasonable Effectiveness of Contact Tracing on Networks with Cliques

Abbas K. Rizi, Leah Keating, James P. Gleeson, David O'Sullivan, Mikko Kivelä 2023 arXiv.org

Directed percolation in temporal networks

Arash Badie Modiri, Abbas K. Rizi, Marton Karsai, Mikko Kivelä 2022 PHYSICAL REVIEW RESEARCH

Directed percolation in random temporal network models with heterogeneities

Arash Badie-Modiri, Abbas K. Rizi, Márton Karsai, Mikko Kivelä 2022 Physical Review E

Randomized Reference Models for Temporal Networks

Laetitia Gauvin, Mathieu Génois, Márton Karsai, Mikko Kivelä, Taro Takaguchi, Eugenie Valdano, Christian L. Vestergaard 2022 SIAM Review

Herd immunity and epidemic size in networks with vaccination homophily

Takayuki Hiraoka, Abbas K. Rizi, Mikko Kivelä, Jari Saramäki 2022 Physical Review E

Adaptive and optimized COVID-19 vaccination strategies across geographical regions and age groups

Jeta Molla, Alejandro Ponce de León Chávez, Takayuki Hiraoka, Tapio Ala-Nissila, Mikko Kivelä, Lasse Leskelä 2022 PLoS computational biology

Epidemic spreading and digital contact tracing: Effects of heterogeneous mixing and quarantine failures

Abbas K. Rizi, Ali Faqeeh, Arash Badie-Modiri, Mikko Kivelä 2022 Physical Review E