AIPSE supports scientific breakthroughs in projects that combine high-level AI research with high-level physical sciences or engineering research and in which AI plays a central role in facilitating the breakthrough.
The AIPSE Academy Programme coordinates a group of projects funded both under the AIPSE programme call and under the Academy of Finland’s ICT 2023 call "Computation, Machine Learning and Artificial Intelligence".
Different types of data-driven methods are continuing to gain in importance in research, administration and industry. This development owes much to progress in such areas as machine learning, pattern recognition, statistics, data mining and computational and software-based database technology; the much-expanded availability of training materials; and the rapid growth of computing power.
Methods developed in AI research have broad potential application in the science context, and particularly in new lines of multidisciplinary research. The main goal and ambition of the Academy Programme for Novel Applications of Artificial Intelligence in Physical Sciences and Engineering Research (AIPSE) is to deepen and broaden AI research expertise within these disciplines.
The programme’s primary objective is to
- produce scientific breakthroughs in projects that combine high-level AI research with high-level physical sciences or engineering research and in which AI plays a central role in facilitating the breakthrough either in AI research or in physical sciences or engineering research.
Other aims of the programme are to
- identify new areas of application and opportunities for research collaboration in physical sciences and engineering
- promote new kinds of research collaboration and so to regenerate research
- harness data for productive use and actively utilise open data in the projects funded.
Novel Applications of Artificial Intelligence in Physical Sciences and Engineering (AIPSE) 2017, funding €7m, funding period 1 Jan 2018–31 Dec 2021
Below you find a list of projects funded in the AIPSE Academy Programme. You find more information about the funding decisions in WebFocus.
Computational tomographic atomic force microscopy (CATAFM)
- Adam Foster, Aalto University
- Juho Kannala, Aalto University
- Peter Liljeroth, Aalto University
Smart autonomous broadband laser light (SMALL)
- Goery Genty, Tampere University
- Alessandro Foi, Tampere University
Adaptive and intelligent data (AIDA)
- Aristides Gionis, Aalto University
- Jussi Kangasharju, University of Helsinki
Structure prediction of hybrid nanoparticles via artificial intelligence (HNP-AI)
- Hannu Häkkinen, University of Jyväskylä
- Tommi Kärkkäinen, University of Jyväskylä
Intelligent Crop Production: Data-integrative, Multi-task Learning Meets Crop Simulator (AI-CropPro)
- Hiroshi Mamitsuka, Aalto University
- Pirjo Peltonen-Sainio, Natural Resources Institute Finland (LUKE)
Artificial Intelligence for Retrieval of Forest Biomass & Structure (AIROBEST)
- Matti Mõttus, VTT Technical Research Centre of Finland Ltd
- Jorma Laaksonen, Aalto University
Replacing geo-engineering with robust social incentives: a first quantification of complex anthropogenic impact on air quality modeling and interaction with regulations, using agent-based simulations (ANTHRO-IMPACT)
- Nønne Prisle, University of Oulu
Artificial Intelligence for Microscopic Structure Search (AIMSS)
- Patrick Rinke, Aalto University
- Jukka Corander, University of Helsinki
AI spider silk threading (ASSET)
- Quan Zhou, Aalto University
- Markus Linder, Aalto University
- Ville Kyrki, Aalto University
- Tommi Laitinen, Programme Manager, tel. +358 295 335 057
- Juha Latikka, Senior Science Adviser, etl. +358 295 335 058
- Sanna Hytönen, Coordinator, tel. +358 295 335 032
Our email addresses are in the format firstname.lastname(at)aka.fi.