Department of Computer Science

Complex Systems

Complex systems are found at all scales in nature, from the complex machinery operating inside our cells to the human brain, from human sociality to the networked social organization.

Complex Systems is a transdisciplinary research area that builds on statistical physics, computer science, data science, and applied mathematics. Complex systems consist of large numbers of interacting elements, with stochastic interactions and non-trivial interaction structure. They are often outcomes of evolutionary processes, and display rich structures and dynamical phenomena from self-organization to phase transitions.

Complex systems are found at all scales in Nature, from the complex machinery operating inside our cells to the human brain and to various aspects of human sociality and the networked social organization of humans. Intriguingly, these systems are often shaped by forces of similar nature, and therefore understanding one system may provide surprising insights into entirely different domains.

Our faculty has a strong focus on complex networks and network science, with applications in (among others) computational social science, network neuroscience, biomedical sciences and health technology, as well as humanities.


Interested in working with us?

Contact [email protected]

Latest publications

Quantifying daily rhythms with non-negative matrix factorization applied to mobile phone data

Talayeh Aledavood, Ilkka Kivimäki, Sune Lehmann, Jari Saramäki 2022 Scientific Reports


Evgeny Burnaev, Dmitry I. Ignatov, Sergei Ivanov, Michael Khachay, Olessia Koltsova, Andrey Kutuzov, Sergei O. Kuznetsov, Natalia Loukachevitch, Amedeo Napoli, Panos M. Pardalos, Jari Saramäki, Andrey Savchenko, Evgenii Tsymbalov, Elena Tutubalina 2022 Recent Trends in Analysis of Images, Social Networks and Texts

Peripheral differentiation patterns of human T cells

Nelli Heikkilä, Iivo Hetemäki, Silja Sormunen, Helena Isoniemi, Eliisa Kekäläinen, Jari Saramäki, T. Petteri Arstila 2022 EUROPEAN JOURNAL OF IMMUNOLOGY

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

Communication now and then: analyzing the Republic of Letters as a communication network

Javier Ureña-Carrion, Petri Leskinen, Jouni Tuominen, Charles van den Heuvel, Eero Hyvönen, Mikko Kivelä 2022 Applied network science

Effect of manual and digital contact tracing on COVID-19 outbreaks

A. Barrat, C. Cattuto, M. Kivelä, S. Lehmann, J. Saramäki 2021 Journal of the Royal Society Interface

Individual-driven versus interaction-driven burstiness in human dynamics

Jeehye Choi, Takayuki Hiraoka, Hang Hyun Jo 2021 Physical Review E

Characterization of human T cell receptor repertoire data in eight thymus samples and four related blood samples

Nelli Heikkilä, Iivari Kleino, Reetta Vanhanen, Dawit A. Yohannes, Ilkka P. Mattila, Jari Saramäki, T. Petteri Arstila 2021 Data in Brief

Generation of self-reactive, shared T-cell receptor α chains in the human thymus

Nelli Heikkilä, Silja Sormunen, Joonatan Mattila, Taina Härkönen, Mikael Knip, Emmi Leena Ihantola, Tuure Kinnunen, Ilkka P. Mattila, Jari Saramäki, T. Petteri Arstila 2021 JOURNAL OF AUTOIMMUNITY
More information on our research in the Research database.
Research database


Circadian rhythms during a week, graph from research publication

Circadian rhythms

e are currently working on both massive databases of auto-recorded digital data as well as personal sensors (wristbands, bed sensors) to study circadian patterns.

Department of Computer Science
Complex Systems research figure from a publication, Department of Computer Science

Community detection in complex networks

Most networks are not homogenious, meaning that some sets of nodes are more connected among themselves than to the rest of the network. The aim of community detection is to study this mezo-scale structure and devise algorithms that would identify these sets of nodes.

Department of Computer Science
Complex Systems, Aalto University

Public transport networks

In our research project we aim to collect public transport timetable data around the world, curate the data, and publish it in a variety of formats available to be used for both transit planners as well as network scientists.

Department of Computer Science


Much of the work done in the Complex Systems Group that involves empirical networks modeling or method development also involves computational problems that cannot be solved with existing software. We often develop novel algorithms and techniques to push the boundaries of analysis of complex systems. In this page the results of that work is shared in hope that these tools will benefit the research community and other people interested in complex networks.

See our GitHub page for software we have published.


Takayuki Hiraoka

Postdoctoral Researcher

Jari Saramäki

Professorship Saramäki J.
Department of Computer Science
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