Research groups

Bayesian Statistics

Professor Jukka Corander, CI programme

We do research on theoretical and applied machine learning, biometry, bioinformatics and forensic statistics.

Combinatorial Pattern Matching

Professor Esko Ukkonen, ADA programme

The group's mission is to develop combinatorial algorithms for pattern search and synthesis problems for sequential and higher-dimensional data. The group is interested in the basic research of the theoretical aspects of the area as well as in various applications, mostly in bioinformatics.

Complex Systems Computation (CoSCo)

Professor Petri Myllymäki, CI programme

The CoSCo group investigates computational modeling issues in complex systems, and the related implementation aspects, focusing on prediction and model selection tasks. The research areas addressed include Bayesian networks and other probabilistic graphical models, data visualization, and information-theoretic approaches to learning and inference.

Computational Logic

Professor Ilkka Niemelä, CI programme

Computational Logic Group develops automated reasoning techniques for solving challenging computational problems in engineering and science. The current focus is on efficient computational methods for solving large constraint satisfaction problems including SAT, SMT and rule-based constraints and on their applications in areas such as computer aided verification, automated testing, product configuration, planning, combinatorial problems and logical cryptanalysis.

Data Mining

Professor Aristides Gionis, ADA programme

The data-mining group focuses on developing novel methods to extract knowledge from data, designing algorithms to summarize large volumes of data efficiently and effectively, and exploring new ways of using the extracted information. Specific areas of interest include: pattern discovery, clustering and outlier detection, graph mining, social-network analysis, analysis of information networks and social-network dynamics, analysis of smart-city sensor data.

Digital Content Communities (DCC)

Professor Marko Turpeinen. NS programme

Our research focuses on social computing, i.e., information systems that enable and support social creativity, participatory media and distributed problem solving. However, to develop successful new technologies, and bear responsibility of design decisions, we as developers should understand and anticipate the dynamics of technology-society interaction. This requires multi disciplinary end-to-end research from technological platforms to various viewpoints to their impact on the use environment.

Discovery

Professor Hannu Toivonen, ADA programme

The Discovery group develops novel methods and tools for data mining and computational creativity. Its focus is on algorithmic methods for discovering links and patterns in data, and recently also on their use in creative systems. Application areas range from link discovery in bioinformatics to computational generation of poetry.

Distributed and Mobile Cloud Systems

Professor Keijo Heljanko, director of DMC programme

Distributed and Mobile Cloud Systems is a research programme that combines the research activities of the groups of the participating professors: Andrei Gurtov, Keijo Heljanko, Jussi Kangasharju, Sasu Tarkoma and Antti Ylä-Jääski.

Genome-scale Algorithmics

Professor Veli Mäkinen, ADA programme

We develop algorithms and data structures for the analysis of genome-scale data. Such data is abundant due to modern molecular biology measurement techniques like high-throughput sequencing. We are especially interested in applications of compressed data structures, that make it possible to analyse the often highly redundant data within the space of their information content. We also study other scalability aspects like distributed computation/storage around genome-scale data.

Kernel Machines, Pattern Analysis and Computational Biology

Professor Juho Rousu. ADA programme

The group develops machine learning methods, models and tools for computational sciences, in particular computational biology. The methodological backbone of the group is formed by kernel methods and regularized learning. The group particularly focusses in learning with multiple and structured targets, multiple views and ensembles. Applications of interest in computational biology include network reconstruction, gene functional classification as well as mass spectrometry informatics.

Neuroinformatics

Professor Aapo Hyvärinen, ADA programme

Neuroinformatics is broadly defined as the intersection of information technology and neuroscience. Our research goals are to develop new multivariate statistical methods, and to use them to build mathematical models of brain function as well as to analyse neuroscientific data.

New Paradigms in Computing

Professor Petteri Kaski, ADA programme

We perform basic research at the intersection of core computer science (algorithm design and analysis) and discrete mathematics, with an emphasis towards novel techniques and less studied models of computation. We invest substantial effort to high-risk, high-yield research problems of relatively broad theoretical interest, selected on both problem and method driven basis. However, we also aim at rapid publication of more specific, smaller observations. We particularly seek and value solid results with mathematical elegance and simplicity.

Parsimonious Modelling (PM)

Dr Jaakko Hollmén, ADA programme

The research group Parsimonious Modelling develops computational methods for data analysis and applies these methods on two particular application fields: cancer genomics and environmental informatics. Both of these application fields exhibit problems of high dimensional data and complex, unknown interactions between measurements.

Probabilistic Machine Learning

Professor Samuel Kaski, CI programme

The group develops machine learning methods for statistical data mining, information visualization, exploratory data analysis, and in general for probabilistic modeling of data. By machine learning we mean flexible statistical models usable in several applications.

Social Interaction and Emotion (SIE)

Professor Niklas Ravaja, NS programme

The mission of the SIE group is to increase our understanding of ICT-mediated social interaction (e.g., interaction taking place during digital game playing or in social network services).