The algorithms research area studies the paradigms and principles of computation. Our research seeks to establish new mathematical and algorithmic principles by which computation can be efficiently harnessed and understood, such as the introduction of techniques from higher algebra to algorithm design both in the centralised and distributed settings. Key objects of study are representations of information and automated reasoning with the ambition of automating the design and analysis of lower-level algorithmic primitives. We chart the power and the limits of efficient computation in both current and novel computing paradigms, ranging from adversarially fault-tolerant distributed computing to algorithmic biochemistry.






Chris Brzuska


Parinya Chalermsook

approximation algorithms, combinatorial optimisation, discrete mathematics

Mario Di Francesco

wireless networking, mobile and ubiquitous computing, Internet of Things

Aristides Gionis

data mining, graph mining, social-network analysis, social media analysis

Keijo Heljanko

distributed systems, cloud computing, big data, distributed computing

Tomi Janhunen

computational logic, automated reasoning, constraints, constraint-based optimization, learning logical representations from data

Alex Jung

statistical learning theory, compressed sensing, big data, compressed sensing, complex networks, convex optimization, graphical models, distributed algorithms, information theory, dimensionality reduction, statistical physics

Petteri Kaski

algorithm theory, exact and parameterized algorithms, algebraic algorithms, algorithm engineering

Ilkka Niemelä

computational logic, constraints, machine learning, automated reasoning, constraint-based optimization, verification and testing

Pekka Orponen

algorithmics of self-organisation, DNA and RNA self-assembly, stochastic and online algorithms, computational complexity

Jukka Suomela

algorithms, theoretical computer science, distributed and parallel computing, digital humanities











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