Research groups

Adaptive Computing [2]

Dr Patrik Floréen

Adaptive computing focuses on systems that adjust automatically to different situations. Our mission is to conduct research on modelling and optimisation in resource-constrained distributed environments. We work on ubiquitous computing in mobile environments and distributed algorithms with applications to sensor networks.

Bayesian Statistics [3]

Professor Jukka Corander

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

Collaborative Networking [4]

Professor Jussi Kangasharju

Combinatorial Algorithms and Computation [5]

Professor Pekka Orponen

Combinatorial Pattern Matching [6]

Professor Esko Ukkonen

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) [7]

Professor Petri Myllymäki

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 [8]

Professor Ilkka Niemelä

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 [9]

Docent Kai Puolamäki (Acting group leader)

The developments in measurement and data collection technologies have made it possible to gather and store large amounts of information. However, the ability to analyze masses of raw data has increased at a much slower speed. The research programme on data analysis develops data mining and computational statistics methods for various application tasks.

Digital Content Communities (DCC) [10]

Professor Marko Turpeinen, Dr Olli Pitkänen, Dr Anu Kankainen

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 [11]

Professor Hannu Toivonen

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 Networking and Security [12]

Professor Antti Ylä-Jääski

The group focuses on the fundaments of the Internet and the evolution of network systems. In this group we specifically emphasise heterogeneous networks and network architecture evolution primarily from the services and security dimensions. In addition to services and security the third fundamental element to our research is mobile networking.

Genome-scale Algorithmics [13]

Professor Veli Mäkinen

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 [14]

Professor Juho Rousu

Mobile Computing [15]

Professor Sasu Tarkoma

The Mobile Computing Group investigates different aspects of wireless and mobile communications. The group has a strong focus on mobile middleware and service platforms.

Networking Research [16]

Dr Andrei Gurtov

The Networking research group investigates issues related to the architecture of the future internet, especially locator/identifier split and new approaches to establishing trust by overlay networks.

Neuroinformatics [17]

Professor Aapo Hyvärinen

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 [18]

Professor Petteri Kaski

Parsimonious Modelling (PM) [19]

Dr Jaakko Hollmén

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.

Social Interaction and Emotion (SIE) [20]

Professor Niklas Ravaja

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).

Statistical Machine Learning and Bioinformatics [21]

Professor Samuel Kaski

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.

Ubiquitous Interaction (UIx) [22]

Professor Giulio Jacucci

Ubiquitous Interaction (UIx) develops novel interactive applications and studies phenomena related to ubiquitous technologies.

Usable Security, Privacy and Trust (USec) [23]

Dr Kristiina Karvonen

By employing methods provided by the field of human-computer interaction, the group seeks to create and design more usable security that enables maintaining an adequate level of security, privacy and trust among Internet users.