New HIIT programmes 2016-2021
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.
Building Trust in Secure Computing Systems (BURST), Director: Professor Valtteri Niemi
The BURST program starts from the observation that, while digitalization is pervasive, computing systems are still inherently vulnerable. Our objective is to build trust in computing systems and make the underlying platforms verifiable at all stages of lifecycle: design, build, deployment, and also run-time. The approach of BURST is to leverage collective expertise of PIs for achieving build-in pervasive verifiability, combining work in authentication (Aura), attestation (Asokan), cryptographic proofs (Niemi), formal verification (Tripakis), and network/protocol security (Tarkoma). The long-term mission of BURST program, aiming 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.
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 utilized.
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).
HIIT Programmes terminating in 2016
Algorithmic Data Analysis (ADA): Developing advanced data analysis, mining, and modelling methods for different areas of science and technology: combining basic research in computer science with applications. Director: Professor Aristides Gionis
Computational Inference (CI): Computational methods for creating useful information from the massive data sources produced by the current data revolution: pushing the boundary towards more complex problems involving big data, heterogeneous data sources, sructured data models and extremely rapid inference. Director: Professor Jukka Corander
Distributed and Mobile Cloud Systems (DMC): Design, analysis and evaluation of extremely large-scale networked systems. Director: Professor Keijo Heljanko
Network Society (NS): Developing human-centric ubiquitous ICT and anticipating its impact in everyday life. Director: Professor Giulio Jacucci
The publications of HIIT are most typically listed in the researchers' own web pages, and additionally in the publication registers of University of Helsinki and Aalto University.
Last updated on 12 Oct 2016 by Petri Myllymäki - Page created on 21 Apr 2008 by Visa Noronen