# Data science

The data science research area is composed of several research groups that fuse computer science, statistics and applied mathematics to solve application problems in a data-driven manner. The research is fuelled by the data arising from every domain of the modern world: generated by high-throughput biomedical technologies, recorded by ubiquitous IoT sensors, or stored by providers of online services for analysing customer behaviour. We apply a range of techniques from network science to Bayesian methods and from machine learning to algorithms research to model the data and to create practical applications. Data science is inherently multidisciplinary; our researchers focus on the computational and methodological core and work together with external domain experts. Major application fields are found in bioinformatics, computational social science and astroinformatics. Our research groups have studied, e.g., how to identify metabolites with fast algorithms, how human gut microbiome dynamics relate to type 1 diabetes, and how to estimate travel times in developing countries from mobile-phone data.

## Professors

### Aristides Gionis

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

### Keijo Heljanko

*distributed systems, cloud computing, big data, distributed computing*

### Eero Hyvönen

*semantic web, linked open data, artificial intelligence, web technologies*

### 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 *

### Kimmo Kaski

*computational science, statistical physics, complex systems and networks, social networks, computational social science*

### Petteri Kaski

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

### Samuel Kaski

*machine learning, probabilistic modelling, artificial intelligence, bioinformatics, computational medicine, user interaction, brain signal analysis*

### Mikko Kivelä

*computational science, complex systems*

### Jouko Lampinen

*computational information technology*

### Harri Lähdesmäki

*bioinformatics, probabilistic modelling, machine learning, systems biology*

### Pekka Orponen

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

### Kai Puolamäki

*explorative data analysis, randomization, machine learning*

### Juho Rousu

*predicting structured data, kernel methods, computational biology, machine learning*

### Jari Saramäki

*data science, complex systems, complex networks, social networks, network neuroscience, computational immunology *

### Jukka Suomela

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

### Stavros Tripakis

*formal methods, system design, cyber-physical systems*

### Aki Vehtari

*Bayesian inference, probabilistic modeling, machine learning*