- About us
- News & Events
- Collaboration and partners
- Contact information
- Lift area
Continuous development, curiosity and passion direct our efforts in developing new technologies and finding responsible scientific solutions intended to make a better world. Our research aims to address the increasingly complex challenges faced by society; namely, those associated with energy, the environment, wellbeing, and decision-making.
The school has experienced notable success in terms of the national and international funding it receives. There are six Academy of Finland Centres of Excellence at the school, and twelve researchers are currently funded by the European Research Council, ERC. In addition, there are three Academicians of Science and five Academy of Finland Professors at the school. The school is involved in two broad-ranging Flagship projects funded by the European Commission (Graphene and the Human Brain Project).
Research conducted at the School of Science generates over 1 000 scientific publications a year.
The broad-ranging and interdisciplinary approach to research taken at the school pervades the university itself and reaches out to our partners through a strong commitment to networking. Within the university, the school's multi-disciplinary research groups work together and in close cooperation with those of Aalto's other schools on projects that seek to address challenges associated with energy and digitisation, for example. World-class research requires a broad-based approach to international networking with the best universities in their respective fields.
The research environments provide access to cutting-edge equipment for neuroimaging (Aalto NeuroImaging), nano-sised structures and materials (Otaniemi Micro and Nanotechnologies), and a low-temperature research facility (Low Temperature Laboratory). All three of the research infrastructures were approved as part of Finland's national strategy and roadmap for research infrastructures 2014–2020.
Eric Malmi will be competing in the Falling Walls Lab competition with research that aims to automatically reconstruct family trees.
The use of smartphones generates ambivalent user experiences – they are seen as both time-saving and time-wasting devices.
Support for configuration of physical products and services
Learning Methods for Variable Selection and Time Series Prediction