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 & Lecturers
Professor Aristides Gionis
data mining, graph mining, social-network analysis, social media analysis
Professor Keijo Heljanko
distributed systems, cloud computing, big data, distributed computing
Professor Eero Hyvönen
semantic web, linked open data, artificial intelligence, web technologies
Lecturer Tomi Janhunen
computational logic, automated reasoning, constraints, constraint-based optimization, learning logical representations from data
Professor 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
Professor Emeritus Kimmo Kaski
computational science, statistical physics, complex systems and networks, social networks, computational social science
Professor Petteri Kaski
algorithm theory, exact and parameterized algorithms, algebraic algorithms, algorithm engineering
Professor Samuel Kaski
machine learning, probabilistic modelling, artificial intelligence, bioinformatics, computational medicine, user interaction, brain signal analysis
Professor Mikko Kivelä
computational science, complex systems
Lecturer Ari Korhonen
algorithm engineering, software visualisation, web technologies, big data, educational data mining, learning analytics, computing education research, educational technology, digital humanities
Professor Jouko Lampinen
computational information technology
Lecturer Riku Linna
stochastic processes and models, complex systems, statistical physics, (nonlinear) dynamics
Professor Harri Lähdesmäki
bioinformatics, probabilistic modelling, machine learning, systems biology
Professor Pekka Orponen
algorithmics of self-organisation, DNA and RNA self-assembly, stochastic and online algorithms, computational complexity
Professor Kai Puolamäki
explorative data analysis, randomization, machine learning
Professor Juho Rousu
predicting structured data, kernel methods, computational biology, machine learning
Professor Jari Saramäki
data science, complex systems, complex networks, social networks, network neuroscience, computational immunology
Professor Jukka Suomela
algorithms, theoretical computer science, distributed and parallel computing, digital humanities
Professor Simo Särkkä (Dept. Electrical Engineering and Automation at Aalto, Affiliated Prof. at Dept. Computer Science)
recursive Bayesian estimation, stochastic dynamic systems, machine learning
Professor Stavros Tripakis
formal methods, system design, cyber-physical systems
Professor Aki Vehtari
bayesian inference, probabilistic modeling, machine learning