In 2017, HIIT supported the following research centres and programmes:
- Finnish Center for Artificial Intelligence (FCAI)
- Foundations of Computational Health (FCHealth)
- Helsinki-Aalto Center for Information Security (HAIC)
- Helsinki Centre for Data Science (HiDATA)
- Augmented Research (AR)
- Computational Inference (COIN)
Finnish Center for Artificial Intelligence (FCAI)
Director: Professor Samuel Kaski
Aalto University and the University of Helsinki have joined forces in artificial intelligence research by establishing the Finnish Center for Artificial Intelligence (FCAI). In partnership with companies and the public sector, FCAI works towards the next generation of AI that is interactive, dependable and data-efficient. It aims to boost and extend AI research and its applications by bringing together universities, industrial actors and the public sector. With our partners in Finland and abroad we want to achieve societal impact by generating business and solutions that will have world-wide positive effects on the economy and the well-being of people.
Foundations of Computational Health (FCHealth)
Director: Professor Juho Rousu
The FCHealth programme aims to solve hard computational challenges faced upon the emerging digitalization and wide adoption of data-driven approaches in healthcare. We combine state-of-the-art computational methods with large-real world data arising in healthcare and personalized medicine, analysed in collaboration with experts from Aalto University, University of Helsinki, Hospital District of Helsinki and Uusimaa (HUS) as well as Institute for Molecular Medicine Finland (FIMM).
HAIC Research Program (HAIC-R)
Director: Professor Valtteri Niemi
HAIC (Helsinki Aalto Center for Information Security) is a strategic initiative set up by Aalto University and the University of Helsinki in June 2016 to ensure excellence in information security research and education. During the last few years, Aalto University and the University of Helsinki have built up strong research groups and education programs in information security and privacy. HIIT hosts the research arm of HAIC as a research program. The long-term mission of the HAIC Research Unit towards the year 2025 is to enable the design, building and deployment of distributed large-scale systems, where each node (component, device, network element etc.) contributes in verifying trustworthiness of the entire system. Each node would also be able to verify whether any other node or even the entire system is trustworthy.
Helsinki Centre for Data Science (HiDATA)
Director: Professor Sasu Tarkoma
Data science, i.e., extraction of knowledge and insights from data, is important across many fields of science. HiDATA, Helsinki Centre for Data Science, aims to create a world-class research and research-based education hub of data science in Helsinki, as a joint effort between the University of Helsinki and Aalto University. HiDATA builds on the existing, strong research in various areas of data science, and aims to provide novel synergies across disciplines. HiDATA is funded in 2017-2021 as part of the profiling measures of the Academy of Finland, the University of Helsinki and Aalto University, and will get to full speed during 2018.
Augmented Research (AR)
Director: Professor Giulio Jacucci
Augmented search, research, and knowledge work are the main themes of the multidisciplinary HIIT-wide research initiative that is a strategic research focus of HIIT. Several research groups ranging from Human-Computer Interaction to Machine Learning and Complex Systems Computation collaborate to produce cutting edge research and demonstrations. The project investigates how Human-Computer Interaction and Probabilistic Machine Learning can be combined to increase, by order of magnitude, the effectiveness of search and knowledge work.
Computational Inference (COIN)
Director: Professor Samuel Kaski
COIN is a research programme in machine learning and probabilistic modelling, which are core technologies of data science. Our main focus is on the new algorithmic methods required for the interrelated challenges of interactive modelling, computational interface design, and precision medicine. The emphasis is on large data collections and computationally demanding modelling and inference algorithms. Our mission is to push the boundary both towards more complex problems, requiring more structured data models, and towards more efficient algorithms, allowing bigger data sets to be utilised.